mirror of
https://github.com/apache/commons-math.git
synced 2025-02-06 18:18:56 +00:00
[MATH-850] Remove deprecated RandomData and RandomDataImpl classes.
This commit is contained in:
Thomas Neidhart
parent
f1b2fcd7f5
commit
76d5be34f0
@ -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;
|
||||
|
||||
@ -38,31 +37,12 @@ public abstract class AbstractIntegerDistribution implements IntegerDistribution
|
||||
/** Serializable version identifier */
|
||||
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);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@ -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.
|
||||
@ -58,16 +50,6 @@ implements RealDistribution, Serializable {
|
||||
/** Solver absolute accuracy for inverse cumulative computation */
|
||||
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);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@ -176,33 +176,6 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
|
||||
this(DEFAULT_BIN_COUNT, generator);
|
||||
}
|
||||
|
||||
/**
|
||||
* 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.
|
||||
|
||||
@ -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;
|
||||
|
||||
}
|
||||
@ -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;
|
||||
|
||||
@ -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));
|
||||
}
|
||||
|
||||
}
|
||||
@ -96,19 +96,6 @@ public class ValueServer {
|
||||
randomData = new RandomDataGenerator();
|
||||
}
|
||||
|
||||
/**
|
||||
* 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.
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user