Reverting commit 8a35ca4f8e as per Gilles request.
The work on revamping the random packages is perfoemd in the random-ravamp branch.
This commit is contained in:
Luc Maisonobe
parent
16f46dcc3d
commit
e0a8ac4fb5
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.random;
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import org.apache.commons.math4.exception.NotStrictlyPositiveException;
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import org.apache.commons.math4.util.FastMath;
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/**
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* Abstract class implementing the {@link RandomGenerator} interface.
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* Default implementations for all methods other than {@link #nextDouble()} and
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* {@link #setSeed(long)} are provided.
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* <p>
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* All data generation methods are based on {@code code nextDouble()}.
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* Concrete implementations <strong>must</strong> override
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* this method and <strong>should</strong> provide better / more
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* performant implementations of the other methods if the underlying PRNG
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* supplies them.</p>
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*
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* @since 1.1
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*/
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public abstract class AbstractRandomGenerator implements RandomGenerator {
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/**
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* Cached random normal value. The default implementation for
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* {@link #nextGaussian} generates pairs of values and this field caches the
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* second value so that the full algorithm is not executed for every
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* activation. The value {@code Double.NaN} signals that there is
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* no cached value. Use {@link #clear} to clear the cached value.
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*/
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private double cachedNormalDeviate = Double.NaN;
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/**
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* Construct a RandomGenerator.
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*/
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public AbstractRandomGenerator() {
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super();
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}
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/**
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* Clears the cache used by the default implementation of
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* {@link #nextGaussian}. Implementations that do not override the
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* default implementation of {@code nextGaussian} should call this
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* method in the implementation of {@link #setSeed(long)}
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*/
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public void clear() {
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cachedNormalDeviate = Double.NaN;
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}
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/** {@inheritDoc} */
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@Override
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public void setSeed(int seed) {
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setSeed((long) seed);
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}
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/** {@inheritDoc} */
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@Override
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public void setSeed(int[] seed) {
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// the following number is the largest prime that fits in 32 bits (it is 2^32 - 5)
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final long prime = 4294967291l;
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long combined = 0l;
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for (int s : seed) {
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combined = combined * prime + s;
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}
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setSeed(combined);
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}
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/**
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* Sets the seed of the underlying random number generator using a
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* {@code long} seed. Sequences of values generated starting with the
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* same seeds should be identical.
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* <p>
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* Implementations that do not override the default implementation of
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* {@code nextGaussian} should include a call to {@link #clear} in the
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* implementation of this method.</p>
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*
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* @param seed the seed value
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*/
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@Override
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public abstract void setSeed(long seed);
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/**
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* Generates random bytes and places them into a user-supplied
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* byte array. The number of random bytes produced is equal to
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* the length of the byte array.
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* <p>
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* The default implementation fills the array with bytes extracted from
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* random integers generated using {@link #nextInt}.</p>
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*
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* @param bytes the non-null byte array in which to put the
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* random bytes
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*/
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@Override
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public void nextBytes(byte[] bytes) {
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// Multiple 4 part of length (i.e. length with two least significant bits unset).
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final int max = bytes.length & 0x7ffffffc;
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int index = 0;
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// Start filling in the byte array, 4 bytes at a time.
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while (index < max) {
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final int random = nextInt();
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bytes[index++] = (byte) random;
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bytes[index++] = (byte) (random >>> 8);
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bytes[index++] = (byte) (random >>> 16);
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bytes[index++] = (byte) (random >>> 24);
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}
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// Fill in the remaining bytes.
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if (index < bytes.length) {
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int random = nextInt();
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while (true) {
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bytes[index++] = (byte) random;
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if (index < bytes.length) {
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random >>>= 8;
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} else {
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break;
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}
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}
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}
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}
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/**
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* Returns the next pseudorandom, uniformly distributed {@code int}
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* value from this random number generator's sequence.
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* All 2<font size="-1"><sup>32</sup></font> possible {@code int} values
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* should be produced with (approximately) equal probability.
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* <p>
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* The default implementation provided here returns
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* <pre>
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* <code>(int) (nextDouble() * Integer.MAX_VALUE)</code>
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* </pre></p>
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*
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* @return the next pseudorandom, uniformly distributed {@code int}
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* value from this random number generator's sequence
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*/
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@Override
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public int nextInt() {
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return (int) ((2d * nextDouble() - 1d) * Integer.MAX_VALUE);
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}
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/**
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* Returns a pseudorandom, uniformly distributed {@code int} value
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* between 0 (inclusive) and the specified value (exclusive), drawn from
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* this random number generator's sequence.
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* <p>
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* The default implementation returns
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* <pre>
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* <code>(int) (nextDouble() * n</code>
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* </pre></p>
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*
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* @param n the bound on the random number to be returned. Must be
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* positive.
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* @return a pseudorandom, uniformly distributed {@code int}
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* value between 0 (inclusive) and n (exclusive).
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* @throws NotStrictlyPositiveException if {@code n <= 0}.
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*/
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@Override
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public int nextInt(int n) {
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if (n <= 0 ) {
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throw new NotStrictlyPositiveException(n);
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}
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int result = (int) (nextDouble() * n);
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return result < n ? result : n - 1;
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}
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/**
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* Returns the next pseudorandom, uniformly distributed {@code long}
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* value from this random number generator's sequence. All
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* 2<font size="-1"><sup>64</sup></font> possible {@code long} values
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* should be produced with (approximately) equal probability.
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* <p>
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* The default implementation returns
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* <pre>
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* <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
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* </pre></p>
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*
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* @return the next pseudorandom, uniformly distributed {@code long}
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*value from this random number generator's sequence
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*/
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@Override
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public long nextLong() {
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return (long) ((2d * nextDouble() - 1d) * Long.MAX_VALUE);
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}
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/**
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* Returns the next pseudorandom, uniformly distributed
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* {@code boolean} value from this random number generator's
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* sequence.
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* <p>
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* The default implementation returns
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* <pre>
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* <code>nextDouble() <= 0.5</code>
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* </pre></p>
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*
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* @return the next pseudorandom, uniformly distributed
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* {@code boolean} value from this random number generator's
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* sequence
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*/
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@Override
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public boolean nextBoolean() {
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return nextDouble() <= 0.5;
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}
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/**
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* Returns the next pseudorandom, uniformly distributed {@code float}
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* value between {@code 0.0} and {@code 1.0} from this random
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* number generator's sequence.
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* <p>
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* The default implementation returns
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* <pre>
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* <code>(float) nextDouble() </code>
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* </pre></p>
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*
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* @return the next pseudorandom, uniformly distributed {@code float}
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* value between {@code 0.0} and {@code 1.0} from this
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* random number generator's sequence
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*/
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@Override
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public float nextFloat() {
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return (float) nextDouble();
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}
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/**
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* Returns the next pseudorandom, uniformly distributed
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* {@code double} value between {@code 0.0} and
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* {@code 1.0} from this random number generator's sequence.
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* <p>
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* This method provides the underlying source of random data used by the
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* other methods.</p>
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*
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* @return the next pseudorandom, uniformly distributed
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* {@code double} value between {@code 0.0} and
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* {@code 1.0} from this random number generator's sequence
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*/
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@Override
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public abstract double nextDouble();
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/**
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* Returns the next pseudorandom, Gaussian ("normally") distributed
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* {@code double} value with mean {@code 0.0} and standard
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* deviation {@code 1.0} from this random number generator's sequence.
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* <p>
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* The default implementation uses the <em>Polar Method</em>
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* due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in
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* D. Knuth, <u>The Art of Computer Programming</u>, 3.4.1C.</p>
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* <p>
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* The algorithm generates a pair of independent random values. One of
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* these is cached for reuse, so the full algorithm is not executed on each
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* activation. Implementations that do not override this method should
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* make sure to call {@link #clear} to clear the cached value in the
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* implementation of {@link #setSeed(long)}.</p>
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*
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* @return the next pseudorandom, Gaussian ("normally") distributed
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* {@code double} value with mean {@code 0.0} and
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* standard deviation {@code 1.0} from this random number
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* generator's sequence
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*/
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@Override
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public double nextGaussian() {
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if (!Double.isNaN(cachedNormalDeviate)) {
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double dev = cachedNormalDeviate;
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cachedNormalDeviate = Double.NaN;
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return dev;
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}
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double v1 = 0;
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double v2 = 0;
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double s = 1;
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while (s >=1 ) {
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v1 = 2 * nextDouble() - 1;
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v2 = 2 * nextDouble() - 1;
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s = v1 * v1 + v2 * v2;
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}
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if (s != 0) {
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s = FastMath.sqrt(-2 * FastMath.log(s) / s);
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}
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cachedNormalDeviate = v2 * s;
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return v1 * s;
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}
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}
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@ -0,0 +1,39 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.random;
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import org.apache.commons.math4.random.RandomGenerator;
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/**
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* Test cases for the AbstractRandomGenerator class.
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*
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*/
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public class AbstractRandomGeneratorTest extends RandomGeneratorAbstractTest {
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public AbstractRandomGeneratorTest() {
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super();
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}
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@Override
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protected RandomGenerator makeGenerator() {
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RandomGenerator generator = new TestRandomGenerator();
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generator.setSeed(1001);
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return generator;
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}
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}
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@ -0,0 +1,43 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.random;
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import java.util.Random;
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import org.apache.commons.math4.random.AbstractRandomGenerator;
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/**
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* Dummy AbstractRandomGenerator concrete subclass that just wraps a
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* java.util.Random instance. Used by AbstractRandomGeneratorTest to test
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* default implementations in AbstractRandomGenerator.
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*
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*/
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public class TestRandomGenerator extends AbstractRandomGenerator {
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private Random random = new Random();
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@Override
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public void setSeed(long seed) {
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clear();
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random.setSeed(seed);
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}
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@Override
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public double nextDouble() {
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return random.nextDouble();
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}
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}
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