Repository: commons-math Updated Branches: refs/heads/master f1b2fcd7f -> 76d5be34f
[MATH-850] Remove deprecated RandomData and RandomDataImpl classes. Project: http://git-wip-us.apache.org/repos/asf/commons-math/repo Commit: http://git-wip-us.apache.org/repos/asf/commons-math/commit/76d5be34 Tree: http://git-wip-us.apache.org/repos/asf/commons-math/tree/76d5be34 Diff: http://git-wip-us.apache.org/repos/asf/commons-math/diff/76d5be34 Branch: refs/heads/master Commit: 76d5be34f0327c8d39015d2962005babc2652cf7 Parents: f1b2fcd Author: Thomas Neidhart <thomas.neidh...@gmail.com> Authored: Thu Feb 19 23:28:28 2015 +0100 Committer: Thomas Neidhart <thomas.neidh...@gmail.com> Committed: Thu Feb 19 23:28:28 2015 +0100 ---------------------------------------------------------------------- .../AbstractIntegerDistribution.java | 21 - .../distribution/AbstractRealDistribution.java | 19 - .../math4/random/EmpiricalDistribution.java | 27 - .../apache/commons/math4/random/RandomData.java | 264 --------- .../math4/random/RandomDataGenerator.java | 8 +- .../commons/math4/random/RandomDataImpl.java | 585 ------------------- .../commons/math4/random/ValueServer.java | 13 - 7 files changed, 4 insertions(+), 933 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/distribution/AbstractIntegerDistribution.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/distribution/AbstractIntegerDistribution.java b/src/main/java/org/apache/commons/math4/distribution/AbstractIntegerDistribution.java index eccf9e7..adaed88 100644 --- a/src/main/java/org/apache/commons/math4/distribution/AbstractIntegerDistribution.java +++ b/src/main/java/org/apache/commons/math4/distribution/AbstractIntegerDistribution.java @@ -23,7 +23,6 @@ import org.apache.commons.math4.exception.NotStrictlyPositiveException; import org.apache.commons.math4.exception.NumberIsTooLargeException; import org.apache.commons.math4.exception.OutOfRangeException; import org.apache.commons.math4.exception.util.LocalizedFormats; -import org.apache.commons.math4.random.RandomDataImpl; import org.apache.commons.math4.random.RandomGenerator; import org.apache.commons.math4.util.FastMath; @@ -39,31 +38,12 @@ public abstract class AbstractIntegerDistribution implements IntegerDistribution private static final long serialVersionUID = -1146319659338487221L; /** - * RandomData instance used to generate samples from the distribution. - * @deprecated As of 3.1, to be removed in 4.0. Please use the - * {@link #random} instance variable instead. - */ - @Deprecated - protected final RandomDataImpl randomData = new RandomDataImpl(); - - /** * RNG instance used to generate samples from the distribution. * @since 3.1 */ protected final RandomGenerator random; /** - * @deprecated As of 3.1, to be removed in 4.0. Please use - * {@link #AbstractIntegerDistribution(RandomGenerator)} instead. - */ - @Deprecated - protected AbstractIntegerDistribution() { - // Legacy users are only allowed to access the deprecated "randomData". - // New users are forbidden to use this constructor. - random = null; - } - - /** * @param rng Random number generator. * @since 3.1 */ @@ -178,7 +158,6 @@ public abstract class AbstractIntegerDistribution implements IntegerDistribution /** {@inheritDoc} */ public void reseedRandomGenerator(long seed) { random.setSeed(seed); - randomData.reSeed(seed); } /** http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/distribution/AbstractRealDistribution.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/distribution/AbstractRealDistribution.java b/src/main/java/org/apache/commons/math4/distribution/AbstractRealDistribution.java index f1e0233..297da1a 100644 --- a/src/main/java/org/apache/commons/math4/distribution/AbstractRealDistribution.java +++ b/src/main/java/org/apache/commons/math4/distribution/AbstractRealDistribution.java @@ -24,7 +24,6 @@ import org.apache.commons.math4.exception.NotStrictlyPositiveException; import org.apache.commons.math4.exception.NumberIsTooLargeException; import org.apache.commons.math4.exception.OutOfRangeException; import org.apache.commons.math4.exception.util.LocalizedFormats; -import org.apache.commons.math4.random.RandomDataImpl; import org.apache.commons.math4.random.RandomGenerator; import org.apache.commons.math4.util.FastMath; @@ -41,13 +40,6 @@ implements RealDistribution, Serializable { public static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY = 1e-6; /** Serializable version identifier */ private static final long serialVersionUID = -38038050983108802L; - /** - * RandomData instance used to generate samples from the distribution. - * @deprecated As of 3.1, to be removed in 4.0. Please use the - * {@link #random} instance variable instead. - */ - @Deprecated - protected RandomDataImpl randomData = new RandomDataImpl(); /** * RNG instance used to generate samples from the distribution. @@ -59,16 +51,6 @@ implements RealDistribution, Serializable { private double solverAbsoluteAccuracy = SOLVER_DEFAULT_ABSOLUTE_ACCURACY; /** - * @deprecated As of 3.1, to be removed in 4.0. Please use - * {@link #AbstractRealDistribution(RandomGenerator)} instead. - */ - @Deprecated - protected AbstractRealDistribution() { - // Legacy users are only allowed to access the deprecated "randomData". - // New users are forbidden to use this constructor. - random = null; - } - /** * @param rng Random number generator. * @since 3.1 */ @@ -243,7 +225,6 @@ implements RealDistribution, Serializable { /** {@inheritDoc} */ public void reseedRandomGenerator(long seed) { random.setSeed(seed); - randomData.reSeed(seed); } /** http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/random/EmpiricalDistribution.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/EmpiricalDistribution.java b/src/main/java/org/apache/commons/math4/random/EmpiricalDistribution.java index 7997181..5e0e842 100644 --- a/src/main/java/org/apache/commons/math4/random/EmpiricalDistribution.java +++ b/src/main/java/org/apache/commons/math4/random/EmpiricalDistribution.java @@ -177,33 +177,6 @@ public class EmpiricalDistribution extends AbstractRealDistribution { } /** - * Creates a new EmpiricalDistribution with the specified bin count using the - * provided {@link RandomDataImpl} instance as the source of random data. - * - * @param binCount number of bins - * @param randomData random data generator (may be null, resulting in default JDK generator) - * @since 3.0 - * @deprecated As of 3.1. Please use {@link #EmpiricalDistribution(int,RandomGenerator)} instead. - */ - @Deprecated - public EmpiricalDistribution(int binCount, RandomDataImpl randomData) { - this(binCount, randomData.getDelegate()); - } - - /** - * Creates a new EmpiricalDistribution with default bin count using the - * provided {@link RandomDataImpl} as the source of random data. - * - * @param randomData random data generator (may be null, resulting in default JDK generator) - * @since 3.0 - * @deprecated As of 3.1. Please use {@link #EmpiricalDistribution(RandomGenerator)} instead. - */ - @Deprecated - public EmpiricalDistribution(RandomDataImpl randomData) { - this(DEFAULT_BIN_COUNT, randomData); - } - - /** * Private constructor to allow lazy initialisation of the RNG contained * in the {@link #randomData} instance variable. * http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/random/RandomData.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/RandomData.java b/src/main/java/org/apache/commons/math4/random/RandomData.java deleted file mode 100644 index 9f862f1..0000000 --- a/src/main/java/org/apache/commons/math4/random/RandomData.java +++ /dev/null @@ -1,264 +0,0 @@ -/* - * 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.math4.random; -import java.util.Collection; - -import org.apache.commons.math4.exception.NotANumberException; -import org.apache.commons.math4.exception.NotFiniteNumberException; -import org.apache.commons.math4.exception.NotStrictlyPositiveException; -import org.apache.commons.math4.exception.NumberIsTooLargeException; - -/** - * Random data generation utilities. - * @deprecated to be removed in 4.0. Use {@link RandomDataGenerator} directly - */ -@Deprecated -public interface RandomData { - /** - * Generates a random string of hex characters of length {@code len}. - * <p> - * The generated string will be random, but not cryptographically - * secure. To generate cryptographically secure strings, use - * {@link #nextSecureHexString(int)}. - * </p> - * - * @param len the length of the string to be generated - * @return a random string of hex characters of length {@code len} - * @throws NotStrictlyPositiveException - * if {@code len <= 0} - */ - String nextHexString(int len) throws NotStrictlyPositiveException; - - /** - * Generates a uniformly distributed random integer between {@code lower} - * and {@code upper} (endpoints included). - * <p> - * The generated integer will be random, but not cryptographically secure. - * To generate cryptographically secure integer sequences, use - * {@link #nextSecureInt(int, int)}. - * </p> - * - * @param lower lower bound for generated integer - * @param upper upper bound for generated integer - * @return a random integer greater than or equal to {@code lower} - * and less than or equal to {@code upper} - * @throws NumberIsTooLargeException if {@code lower >= upper} - */ - int nextInt(int lower, int upper) throws NumberIsTooLargeException; - - /** - * Generates a uniformly distributed random long integer between - * {@code lower} and {@code upper} (endpoints included). - * <p> - * The generated long integer values will be random, but not - * cryptographically secure. To generate cryptographically secure sequences - * of longs, use {@link #nextSecureLong(long, long)}. - * </p> - * - * @param lower lower bound for generated long integer - * @param upper upper bound for generated long integer - * @return a random long integer greater than or equal to {@code lower} and - * less than or equal to {@code upper} - * @throws NumberIsTooLargeException if {@code lower >= upper} - */ - long nextLong(long lower, long upper) throws NumberIsTooLargeException; - - /** - * Generates a random string of hex characters from a secure random - * sequence. - * <p> - * If cryptographic security is not required, use - * {@link #nextHexString(int)}. - * </p> - * - * @param len the length of the string to be generated - * @return a random string of hex characters of length {@code len} - * @throws NotStrictlyPositiveException if {@code len <= 0} - */ - String nextSecureHexString(int len) throws NotStrictlyPositiveException; - - /** - * Generates a uniformly distributed random integer between {@code lower} - * and {@code upper} (endpoints included) from a secure random sequence. - * <p> - * Sequences of integers generated using this method will be - * cryptographically secure. If cryptographic security is not required, - * {@link #nextInt(int, int)} should be used instead of this method.</p> - * <p> - * <strong>Definition</strong>: - * <a href="http://en.wikipedia.org/wiki/Cryptographically_secure_pseudo-random_number_generator";> - * Secure Random Sequence</a></p> - * - * @param lower lower bound for generated integer - * @param upper upper bound for generated integer - * @return a random integer greater than or equal to {@code lower} and less - * than or equal to {@code upper}. - * @throws NumberIsTooLargeException if {@code lower >= upper}. - */ - int nextSecureInt(int lower, int upper) throws NumberIsTooLargeException; - - /** - * Generates a uniformly distributed random long integer between - * {@code lower} and {@code upper} (endpoints included) from a secure random - * sequence. - * <p> - * Sequences of long values generated using this method will be - * cryptographically secure. If cryptographic security is not required, - * {@link #nextLong(long, long)} should be used instead of this method.</p> - * <p> - * <strong>Definition</strong>: - * <a href="http://en.wikipedia.org/wiki/Cryptographically_secure_pseudo-random_number_generator";> - * Secure Random Sequence</a></p> - * - * @param lower lower bound for generated integer - * @param upper upper bound for generated integer - * @return a random long integer greater than or equal to {@code lower} and - * less than or equal to {@code upper}. - * @throws NumberIsTooLargeException if {@code lower >= upper}. - */ - long nextSecureLong(long lower, long upper) throws NumberIsTooLargeException; - - /** - * Generates a random value from the Poisson distribution with the given - * mean. - * <p> - * <strong>Definition</strong>: - * <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda366j.htm";> - * Poisson Distribution</a></p> - * - * @param mean the mean of the Poisson distribution - * @return a random value following the specified Poisson distribution - * @throws NotStrictlyPositiveException if {@code mean <= 0}. - */ - long nextPoisson(double mean) throws NotStrictlyPositiveException; - - /** - * Generates a random value from the Normal (or Gaussian) distribution with - * specified mean and standard deviation. - * <p> - * <strong>Definition</strong>: - * <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda3661.htm";> - * Normal Distribution</a></p> - * - * @param mu the mean of the distribution - * @param sigma the standard deviation of the distribution - * @return a random value following the specified Gaussian distribution - * @throws NotStrictlyPositiveException if {@code sigma <= 0}. - */ - double nextGaussian(double mu, double sigma) throws NotStrictlyPositiveException; - - /** - * Generates a random value from the exponential distribution - * with specified mean. - * <p> - * <strong>Definition</strong>: - * <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda3667.htm";> - * Exponential Distribution</a></p> - * - * @param mean the mean of the distribution - * @return a random value following the specified exponential distribution - * @throws NotStrictlyPositiveException if {@code mean <= 0}. - */ - double nextExponential(double mean) throws NotStrictlyPositiveException; - - /** - * Generates a uniformly distributed random value from the open interval - * {@code (lower, upper)} (i.e., endpoints excluded). - * <p> - * <strong>Definition</strong>: - * <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda3662.htm";> - * Uniform Distribution</a> {@code lower} and {@code upper - lower} are the - * <a href = "http://www.itl.nist.gov/div898/handbook/eda/section3/eda364.htm";> - * location and scale parameters</a>, respectively.</p> - * - * @param lower the exclusive lower bound of the support - * @param upper the exclusive upper bound of the support - * @return a uniformly distributed random value between lower and upper - * (exclusive) - * @throws NumberIsTooLargeException if {@code lower >= upper} - * @throws NotFiniteNumberException if one of the bounds is infinite - * @throws NotANumberException if one of the bounds is NaN - */ - double nextUniform(double lower, double upper) - throws NumberIsTooLargeException, NotFiniteNumberException, NotANumberException; - - /** - * Generates a uniformly distributed random value from the interval - * {@code (lower, upper)} or the interval {@code [lower, upper)}. The lower - * bound is thus optionally included, while the upper bound is always - * excluded. - * <p> - * <strong>Definition</strong>: - * <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda3662.htm";> - * Uniform Distribution</a> {@code lower} and {@code upper - lower} are the - * <a href = "http://www.itl.nist.gov/div898/handbook/eda/section3/eda364.htm";> - * location and scale parameters</a>, respectively.</p> - * - * @param lower the lower bound of the support - * @param upper the exclusive upper bound of the support - * @param lowerInclusive {@code true} if the lower bound is inclusive - * @return uniformly distributed random value in the {@code (lower, upper)} - * interval, if {@code lowerInclusive} is {@code false}, or in the - * {@code [lower, upper)} interval, if {@code lowerInclusive} is - * {@code true} - * @throws NumberIsTooLargeException if {@code lower >= upper} - * @throws NotFiniteNumberException if one of the bounds is infinite - * @throws NotANumberException if one of the bounds is NaN - */ - double nextUniform(double lower, double upper, boolean lowerInclusive) - throws NumberIsTooLargeException, NotFiniteNumberException, NotANumberException; - - /** - * Generates an integer array of length {@code k} whose entries are selected - * randomly, without repetition, from the integers {@code 0, ..., n - 1} - * (inclusive). - * <p> - * Generated arrays represent permutations of {@code n} taken {@code k} at a - * time.</p> - * - * @param n the domain of the permutation - * @param k the size of the permutation - * @return a random {@code k}-permutation of {@code n}, as an array of - * integers - * @throws NumberIsTooLargeException if {@code k > n}. - * @throws NotStrictlyPositiveException if {@code k <= 0}. - */ - int[] nextPermutation(int n, int k) - throws NumberIsTooLargeException, NotStrictlyPositiveException; - - /** - * Returns an array of {@code k} objects selected randomly from the - * Collection {@code c}. - * <p> - * Sampling from {@code c} is without replacement; but if {@code c} contains - * identical objects, the sample may include repeats. If all elements of - * {@code c} are distinct, the resulting object array represents a - * <a href="http://rkb.home.cern.ch/rkb/AN16pp/node250.html#SECTION0002500000000000000000";> - * Simple Random Sample</a> of size {@code k} from the elements of - * {@code c}.</p> - * - * @param c the collection to be sampled - * @param k the size of the sample - * @return a random sample of {@code k} elements from {@code c} - * @throws NumberIsTooLargeException if {@code k > c.size()}. - * @throws NotStrictlyPositiveException if {@code k <= 0}. - */ - Object[] nextSample(Collection<?> c, int k) - throws NumberIsTooLargeException, NotStrictlyPositiveException; - -} http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/random/RandomDataGenerator.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/RandomDataGenerator.java b/src/main/java/org/apache/commons/math4/random/RandomDataGenerator.java index 34765aa..b862103 100644 --- a/src/main/java/org/apache/commons/math4/random/RandomDataGenerator.java +++ b/src/main/java/org/apache/commons/math4/random/RandomDataGenerator.java @@ -49,7 +49,7 @@ import org.apache.commons.math4.exception.util.LocalizedFormats; import org.apache.commons.math4.util.MathArrays; /** - * Implements the {@link RandomData} interface using a {@link RandomGenerator} + * Generates random deviates and other random data using a {@link RandomGenerator} * instance to generate non-secure data and a {@link java.security.SecureRandom} * instance to provide data for the <code>nextSecureXxx</code> methods. If no * <code>RandomGenerator</code> is provided in the constructor, the default is @@ -72,7 +72,7 @@ import org.apache.commons.math4.util.MathArrays; * Instance variables are used to maintain <code>RandomGenerator</code> and * <code>SecureRandom</code> instances used in data generation. Therefore, to * generate a random sequence of values or strings, you should use just - * <strong>one</strong> <code>RandomDataImpl</code> instance repeatedly.</li> + * <strong>one</strong> <code>RandomDataGenerator</code> instance repeatedly.</li> * <li> * The "secure" methods are *much* slower. These should be used only when a * cryptographically secure random sequence is required. A secure random @@ -82,7 +82,7 @@ import org.apache.commons.math4.util.MathArrays; * knowledge of values generated up to any point in the sequence does not make * it any easier to predict subsequent values.</li> * <li> - * When a new <code>RandomDataImpl</code> is created, the underlying random + * When a new <code>RandomDataGenerator</code> is created, the underlying random * number generators are <strong>not</strong> initialized. If you do not * explicitly seed the default non-secure generator, it is seeded with the * current time in milliseconds plus the system identity hash code on first use. @@ -109,7 +109,7 @@ import org.apache.commons.math4.util.MathArrays; * </p> * @since 3.1 */ -public class RandomDataGenerator implements RandomData, Serializable { +public class RandomDataGenerator implements Serializable { /** Serializable version identifier */ private static final long serialVersionUID = -626730818244969716L; http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/random/RandomDataImpl.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/RandomDataImpl.java b/src/main/java/org/apache/commons/math4/random/RandomDataImpl.java deleted file mode 100644 index df2c699..0000000 --- a/src/main/java/org/apache/commons/math4/random/RandomDataImpl.java +++ /dev/null @@ -1,585 +0,0 @@ -/* - * 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.math4.random; - -import java.io.Serializable; -import java.security.NoSuchAlgorithmException; -import java.security.NoSuchProviderException; -import java.util.Collection; - -import org.apache.commons.math4.distribution.IntegerDistribution; -import org.apache.commons.math4.distribution.RealDistribution; -import org.apache.commons.math4.exception.MathIllegalArgumentException; -import org.apache.commons.math4.exception.NotANumberException; -import org.apache.commons.math4.exception.NotFiniteNumberException; -import org.apache.commons.math4.exception.NotPositiveException; -import org.apache.commons.math4.exception.NotStrictlyPositiveException; -import org.apache.commons.math4.exception.NumberIsTooLargeException; -import org.apache.commons.math4.exception.OutOfRangeException; - -/** - * Generates random deviates and other random data using a {@link RandomGenerator} - * instance to generate non-secure data and a {@link java.security.SecureRandom} - * instance to provide data for the <code>nextSecureXxx</code> methods. If no - * <code>RandomGenerator</code> is provided in the constructor, the default is - * to use a {@link Well19937c} generator. To plug in a different - * implementation, either implement <code>RandomGenerator</code> directly or - * extend {@link AbstractRandomGenerator}. - * <p> - * Supports reseeding the underlying pseudo-random number generator (PRNG). The - * <code>SecurityProvider</code> and <code>Algorithm</code> used by the - * <code>SecureRandom</code> instance can also be reset. - * </p> - * <p> - * For details on the default PRNGs, see {@link java.util.Random} and - * {@link java.security.SecureRandom}. - * </p> - * <p> - * <strong>Usage Notes</strong>: - * <ul> - * <li> - * Instance variables are used to maintain <code>RandomGenerator</code> and - * <code>SecureRandom</code> instances used in data generation. Therefore, to - * generate a random sequence of values or strings, you should use just - * <strong>one</strong> <code>RandomDataGenerator</code> instance repeatedly.</li> - * <li> - * The "secure" methods are *much* slower. These should be used only when a - * cryptographically secure random sequence is required. A secure random - * sequence is a sequence of pseudo-random values which, in addition to being - * well-dispersed (so no subsequence of values is an any more likely than other - * subsequence of the the same length), also has the additional property that - * knowledge of values generated up to any point in the sequence does not make - * it any easier to predict subsequent values.</li> - * <li> - * When a new <code>RandomDataGenerator</code> is created, the underlying random - * number generators are <strong>not</strong> initialized. If you do not - * explicitly seed the default non-secure generator, it is seeded with the - * current time in milliseconds plus the system identity hash code on first use. - * The same holds for the secure generator. If you provide a <code>RandomGenerator</code> - * to the constructor, however, this generator is not reseeded by the constructor - * nor is it reseeded on first use.</li> - * <li> - * The <code>reSeed</code> and <code>reSeedSecure</code> methods delegate to the - * corresponding methods on the underlying <code>RandomGenerator</code> and - * <code>SecureRandom</code> instances. Therefore, <code>reSeed(long)</code> - * fully resets the initial state of the non-secure random number generator (so - * that reseeding with a specific value always results in the same subsequent - * random sequence); whereas reSeedSecure(long) does <strong>not</strong> - * reinitialize the secure random number generator (so secure sequences started - * with calls to reseedSecure(long) won't be identical).</li> - * <li> - * This implementation is not synchronized. The underlying <code>RandomGenerator</code> - * or <code>SecureRandom</code> instances are not protected by synchronization and - * are not guaranteed to be thread-safe. Therefore, if an instance of this class - * is concurrently utilized by multiple threads, it is the responsibility of - * client code to synchronize access to seeding and data generation methods. - * </li> - * </ul> - * </p> - * @deprecated to be removed in 4.0. Use {@link RandomDataGenerator} instead - */ -@Deprecated -public class RandomDataImpl implements RandomData, Serializable { - - /** Serializable version identifier */ - private static final long serialVersionUID = -626730818244969716L; - - /** RandomDataGenerator delegate */ - private final RandomDataGenerator delegate; - - /** - * Construct a RandomDataImpl, using a default random generator as the source - * of randomness. - * - * <p>The default generator is a {@link Well19937c} seeded - * with {@code System.currentTimeMillis() + System.identityHashCode(this))}. - * The generator is initialized and seeded on first use.</p> - */ - public RandomDataImpl() { - delegate = new RandomDataGenerator(); - } - - /** - * Construct a RandomDataImpl using the supplied {@link RandomGenerator} as - * the source of (non-secure) random data. - * - * @param rand the source of (non-secure) random data - * (may be null, resulting in the default generator) - * @since 1.1 - */ - public RandomDataImpl(RandomGenerator rand) { - delegate = new RandomDataGenerator(rand); - } - - /** - * @return the delegate object. - * @deprecated To be removed in 4.0. - */ - @Deprecated - RandomDataGenerator getDelegate() { - return delegate; - } - - /** - * {@inheritDoc} - * <p> - * <strong>Algorithm Description:</strong> hex strings are generated using a - * 2-step process. - * <ol> - * <li>{@code len / 2 + 1} binary bytes are generated using the underlying - * Random</li> - * <li>Each binary byte is translated into 2 hex digits</li> - * </ol> - * </p> - * - * @param len the desired string length. - * @return the random string. - * @throws NotStrictlyPositiveException if {@code len <= 0}. - */ - public String nextHexString(int len) throws NotStrictlyPositiveException { - return delegate.nextHexString(len); - } - - /** {@inheritDoc} */ - public int nextInt(int lower, int upper) throws NumberIsTooLargeException { - return delegate.nextInt(lower, upper); - } - - /** {@inheritDoc} */ - public long nextLong(long lower, long upper) throws NumberIsTooLargeException { - return delegate.nextLong(lower, upper); - } - - /** - * {@inheritDoc} - * <p> - * <strong>Algorithm Description:</strong> hex strings are generated in - * 40-byte segments using a 3-step process. - * <ol> - * <li> - * 20 random bytes are generated using the underlying - * <code>SecureRandom</code>.</li> - * <li> - * SHA-1 hash is applied to yield a 20-byte binary digest.</li> - * <li> - * Each byte of the binary digest is converted to 2 hex digits.</li> - * </ol> - * </p> - */ - public String nextSecureHexString(int len) throws NotStrictlyPositiveException { - return delegate.nextSecureHexString(len); - } - - /** {@inheritDoc} */ - public int nextSecureInt(int lower, int upper) throws NumberIsTooLargeException { - return delegate.nextSecureInt(lower, upper); - } - - /** {@inheritDoc} */ - public long nextSecureLong(long lower, long upper) throws NumberIsTooLargeException { - return delegate.nextSecureLong(lower,upper); - } - - /** - * {@inheritDoc} - * <p> - * <strong>Algorithm Description</strong>: - * <ul><li> For small means, uses simulation of a Poisson process - * using Uniform deviates, as described - * <a href="http://irmi.epfl.ch/cmos/Pmmi/interactive/rng7.htm";> here.</a> - * The Poisson process (and hence value returned) is bounded by 1000 * mean.</li> - * - * <li> For large means, uses the rejection algorithm described in <br/> - * Devroye, Luc. (1981).<i>The Computer Generation of Poisson Random Variables</i> - * <strong>Computing</strong> vol. 26 pp. 197-207.</li></ul></p> - */ - public long nextPoisson(double mean) throws NotStrictlyPositiveException { - return delegate.nextPoisson(mean); - } - - /** {@inheritDoc} */ - public double nextGaussian(double mu, double sigma) throws NotStrictlyPositiveException { - return delegate.nextGaussian(mu,sigma); - } - - /** - * {@inheritDoc} - * - * <p> - * <strong>Algorithm Description</strong>: Uses the Algorithm SA (Ahrens) - * from p. 876 in: - * [1]: Ahrens, J. H. and Dieter, U. (1972). Computer methods for - * sampling from the exponential and normal distributions. - * Communications of the ACM, 15, 873-882. - * </p> - */ - public double nextExponential(double mean) throws NotStrictlyPositiveException { - return delegate.nextExponential(mean); - } - - /** - * {@inheritDoc} - * - * <p> - * <strong>Algorithm Description</strong>: scales the output of - * Random.nextDouble(), but rejects 0 values (i.e., will generate another - * random double if Random.nextDouble() returns 0). This is necessary to - * provide a symmetric output interval (both endpoints excluded). - * </p> - */ - public double nextUniform(double lower, double upper) - throws NumberIsTooLargeException, NotFiniteNumberException, NotANumberException { - return delegate.nextUniform(lower, upper); - } - - /** - * {@inheritDoc} - * - * <p> - * <strong>Algorithm Description</strong>: if the lower bound is excluded, - * scales the output of Random.nextDouble(), but rejects 0 values (i.e., - * will generate another random double if Random.nextDouble() returns 0). - * This is necessary to provide a symmetric output interval (both - * endpoints excluded). - * </p> - * @since 3.0 - */ - public double nextUniform(double lower, double upper, boolean lowerInclusive) - throws NumberIsTooLargeException, NotFiniteNumberException, NotANumberException { - return delegate.nextUniform(lower, upper, lowerInclusive); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.BetaDistribution Beta Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param alpha first distribution shape parameter - * @param beta second distribution shape parameter - * @return random value sampled from the beta(alpha, beta) distribution - * @since 2.2 - */ - public double nextBeta(double alpha, double beta) { - return delegate.nextBeta(alpha, beta); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.BinomialDistribution Binomial Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param numberOfTrials number of trials of the Binomial distribution - * @param probabilityOfSuccess probability of success of the Binomial distribution - * @return random value sampled from the Binomial(numberOfTrials, probabilityOfSuccess) distribution - * @since 2.2 - */ - public int nextBinomial(int numberOfTrials, double probabilityOfSuccess) { - return delegate.nextBinomial(numberOfTrials, probabilityOfSuccess); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.CauchyDistribution Cauchy Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param median the median of the Cauchy distribution - * @param scale the scale parameter of the Cauchy distribution - * @return random value sampled from the Cauchy(median, scale) distribution - * @since 2.2 - */ - public double nextCauchy(double median, double scale) { - return delegate.nextCauchy(median, scale); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.ChiSquaredDistribution ChiSquare Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param df the degrees of freedom of the ChiSquare distribution - * @return random value sampled from the ChiSquare(df) distribution - * @since 2.2 - */ - public double nextChiSquare(double df) { - return delegate.nextChiSquare(df); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.FDistribution F Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param numeratorDf the numerator degrees of freedom of the F distribution - * @param denominatorDf the denominator degrees of freedom of the F distribution - * @return random value sampled from the F(numeratorDf, denominatorDf) distribution - * @throws NotStrictlyPositiveException if - * {@code numeratorDf <= 0} or {@code denominatorDf <= 0}. - * @since 2.2 - */ - public double nextF(double numeratorDf, double denominatorDf) throws NotStrictlyPositiveException { - return delegate.nextF(numeratorDf, denominatorDf); - } - - /** - * <p>Generates a random value from the - * {@link org.apache.commons.math4.distribution.GammaDistribution Gamma Distribution}.</p> - * - * <p>This implementation uses the following algorithms: </p> - * - * <p>For 0 < shape < 1: <br/> - * Ahrens, J. H. and Dieter, U., <i>Computer methods for - * sampling from gamma, beta, Poisson and binomial distributions.</i> - * Computing, 12, 223-246, 1974.</p> - * - * <p>For shape >= 1: <br/> - * Marsaglia and Tsang, <i>A Simple Method for Generating - * Gamma Variables.</i> ACM Transactions on Mathematical Software, - * Volume 26 Issue 3, September, 2000.</p> - * - * @param shape the median of the Gamma distribution - * @param scale the scale parameter of the Gamma distribution - * @return random value sampled from the Gamma(shape, scale) distribution - * @throws NotStrictlyPositiveException if {@code shape <= 0} or - * {@code scale <= 0}. - * @since 2.2 - */ - public double nextGamma(double shape, double scale) throws NotStrictlyPositiveException { - return delegate.nextGamma(shape, scale); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.HypergeometricDistribution Hypergeometric Distribution}. - * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion} - * to generate random values. - * - * @param populationSize the population size of the Hypergeometric distribution - * @param numberOfSuccesses number of successes in the population of the Hypergeometric distribution - * @param sampleSize the sample size of the Hypergeometric distribution - * @return random value sampled from the Hypergeometric(numberOfSuccesses, sampleSize) distribution - * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize}, - * or {@code sampleSize > populationSize}. - * @throws NotStrictlyPositiveException if {@code populationSize <= 0}. - * @throws NotPositiveException if {@code numberOfSuccesses < 0}. - * @since 2.2 - */ - public int nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize) - throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException { - return delegate.nextHypergeometric(populationSize, numberOfSuccesses, sampleSize); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.PascalDistribution Pascal Distribution}. - * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion} - * to generate random values. - * - * @param r the number of successes of the Pascal distribution - * @param p the probability of success of the Pascal distribution - * @return random value sampled from the Pascal(r, p) distribution - * @since 2.2 - * @throws NotStrictlyPositiveException if the number of successes is not positive - * @throws OutOfRangeException if the probability of success is not in the - * range {@code [0, 1]}. - */ - public int nextPascal(int r, double p) - throws NotStrictlyPositiveException, OutOfRangeException { - return delegate.nextPascal(r, p); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.TDistribution T Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param df the degrees of freedom of the T distribution - * @return random value from the T(df) distribution - * @since 2.2 - * @throws NotStrictlyPositiveException if {@code df <= 0} - */ - public double nextT(double df) throws NotStrictlyPositiveException { - return delegate.nextT(df); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.WeibullDistribution Weibull Distribution}. - * This implementation uses {@link #nextInversionDeviate(RealDistribution) inversion} - * to generate random values. - * - * @param shape the shape parameter of the Weibull distribution - * @param scale the scale parameter of the Weibull distribution - * @return random value sampled from the Weibull(shape, size) distribution - * @since 2.2 - * @throws NotStrictlyPositiveException if {@code shape <= 0} or - * {@code scale <= 0}. - */ - public double nextWeibull(double shape, double scale) throws NotStrictlyPositiveException { - return delegate.nextWeibull(shape, scale); - } - - /** - * Generates a random value from the {@link org.apache.commons.math4.distribution.ZipfDistribution Zipf Distribution}. - * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion} - * to generate random values. - * - * @param numberOfElements the number of elements of the ZipfDistribution - * @param exponent the exponent of the ZipfDistribution - * @return random value sampled from the Zipf(numberOfElements, exponent) distribution - * @since 2.2 - * @exception NotStrictlyPositiveException if {@code numberOfElements <= 0} - * or {@code exponent <= 0}. - */ - public int nextZipf(int numberOfElements, double exponent) throws NotStrictlyPositiveException { - return delegate.nextZipf(numberOfElements, exponent); - } - - - /** - * Reseeds the random number generator with the supplied seed. - * <p> - * Will create and initialize if null. - * </p> - * - * @param seed - * the seed value to use - */ - public void reSeed(long seed) { - delegate.reSeed(seed); - } - - /** - * Reseeds the secure random number generator with the current time in - * milliseconds. - * <p> - * Will create and initialize if null. - * </p> - */ - public void reSeedSecure() { - delegate.reSeedSecure(); - } - - /** - * Reseeds the secure random number generator with the supplied seed. - * <p> - * Will create and initialize if null. - * </p> - * - * @param seed - * the seed value to use - */ - public void reSeedSecure(long seed) { - delegate.reSeedSecure(seed); - } - - /** - * Reseeds the random number generator with - * {@code System.currentTimeMillis() + System.identityHashCode(this))}. - */ - public void reSeed() { - delegate.reSeed(); - } - - /** - * Sets the PRNG algorithm for the underlying SecureRandom instance using - * the Security Provider API. The Security Provider API is defined in <a - * href = - * "http://java.sun.com/j2se/1.3/docs/guide/security/CryptoSpec.html#AppA";> - * Java Cryptography Architecture API Specification & Reference.</a> - * <p> - * <strong>USAGE NOTE:</strong> This method carries <i>significant</i> - * overhead and may take several seconds to execute. - * </p> - * - * @param algorithm - * the name of the PRNG algorithm - * @param provider - * the name of the provider - * @throws NoSuchAlgorithmException - * if the specified algorithm is not available - * @throws NoSuchProviderException - * if the specified provider is not installed - */ - public void setSecureAlgorithm(String algorithm, String provider) - throws NoSuchAlgorithmException, NoSuchProviderException { - delegate.setSecureAlgorithm(algorithm, provider); - } - - /** - * {@inheritDoc} - * - * <p> - * Uses a 2-cycle permutation shuffle. The shuffling process is described <a - * href="http://www.maths.abdn.ac.uk/~igc/tch/mx4002/notes/node83.html";> - * here</a>. - * </p> - */ - public int[] nextPermutation(int n, int k) - throws NotStrictlyPositiveException, NumberIsTooLargeException { - return delegate.nextPermutation(n, k); - } - - /** - * {@inheritDoc} - * - * <p> - * <strong>Algorithm Description</strong>: Uses a 2-cycle permutation - * shuffle to generate a random permutation of <code>c.size()</code> and - * then returns the elements whose indexes correspond to the elements of the - * generated permutation. This technique is described, and proven to - * generate random samples <a - * href="http://www.maths.abdn.ac.uk/~igc/tch/mx4002/notes/node83.html";> - * here</a> - * </p> - */ - public Object[] nextSample(Collection<?> c, int k) - throws NotStrictlyPositiveException, NumberIsTooLargeException { - return delegate.nextSample(c, k); - } - - /** - * Generate a random deviate from the given distribution using the - * <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling";> inversion method.</a> - * - * @param distribution Continuous distribution to generate a random value from - * @return a random value sampled from the given distribution - * @throws MathIllegalArgumentException if the underlynig distribution throws one - * @since 2.2 - * @deprecated use the distribution's sample() method - */ - @Deprecated - public double nextInversionDeviate(RealDistribution distribution) - throws MathIllegalArgumentException { - return distribution.inverseCumulativeProbability(nextUniform(0, 1)); - - } - - /** - * Generate a random deviate from the given distribution using the - * <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling";> inversion method.</a> - * - * @param distribution Integer distribution to generate a random value from - * @return a random value sampled from the given distribution - * @throws MathIllegalArgumentException if the underlynig distribution throws one - * @since 2.2 - * @deprecated use the distribution's sample() method - */ - @Deprecated - public int nextInversionDeviate(IntegerDistribution distribution) - throws MathIllegalArgumentException { - return distribution.inverseCumulativeProbability(nextUniform(0, 1)); - } - -} http://git-wip-us.apache.org/repos/asf/commons-math/blob/76d5be34/src/main/java/org/apache/commons/math4/random/ValueServer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/ValueServer.java b/src/main/java/org/apache/commons/math4/random/ValueServer.java index a610783..e3132f0 100644 --- a/src/main/java/org/apache/commons/math4/random/ValueServer.java +++ b/src/main/java/org/apache/commons/math4/random/ValueServer.java @@ -97,19 +97,6 @@ public class ValueServer { } /** - * Construct a ValueServer instance using a RandomDataImpl as its source - * of random data. - * - * @param randomData the RandomDataImpl instance used to source random data - * @since 3.0 - * @deprecated use {@link #ValueServer(RandomGenerator)} - */ - @Deprecated - public ValueServer(RandomDataImpl randomData) { - this.randomData = randomData.getDelegate(); - } - - /** * Construct a ValueServer instance using a RandomGenerator as its source * of random data. *
