commons-commits mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From t.@apache.org
Subject [math] [MATH-850] Remove deprecated RandomData and RandomDataImpl classes.
Date Thu, 19 Feb 2015 22:28:43 GMT
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.neidhart@gmail.com>
Authored: Thu Feb 19 23:28:28 2015 +0100
Committer: Thomas Neidhart <thomas.neidhart@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.
      *


Mime
View raw message