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git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141406 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-07-22 02:34:25 +00:00
parent f457a74d08
commit 191ec1a14d
3 changed files with 58 additions and 40 deletions
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4
src/java/org/apache/commons/math/analysis/PolynomialSplineFunction.java
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@ -24,7 +24,7 @@ import org.apache.commons.math.FunctionEvaluationException;
* Represents a polynomial spline function.
* <p>
* A <strong>polynomial spline function</strong> consists of a set of
* <i>interpolating polynomials</i> and an ascending array of domain
* <i>interpolating polynomials</i> and an ascending array of domain
* <i>knot points</i>, determining the intervals over which the spline function
* is defined by the constituent polynomials. The polynomials are assumed to
* have been computed to match the values of another function at the knot
@ -50,7 +50,7 @@ import org.apache.commons.math.FunctionEvaluationException;
* than or equal to <code>x</code>. The value returned is <br>
* <code>polynomials[j](x - knot[j])</code></li></ol>
*
* @version $Revision: 1.8 $ $Date: 2004/07/20 12:55:01 $
* @version $Revision: 1.9 $ $Date: 2004/07/22 02:34:25 $
*/
public class PolynomialSplineFunction implements UnivariateRealFunction, Serializable {

13
src/java/org/apache/commons/math/random/EmpiricalDistribution.java
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@ -43,7 +43,7 @@ import org.apache.commons.math.stat.univariate.StatisticalSummary;
* generate random values "like" those in the input file -- i.e., the values
* generated will follow the distribution of the values in the file.
*
* @version $Revision: 1.21 $ $Date: 2004/07/18 23:57:11 $
* @version $Revision: 1.22 $ $Date: 2004/07/22 02:34:25 $
*/
public interface EmpiricalDistribution {
@ -83,7 +83,9 @@ public interface EmpiricalDistribution {
/**
* Returns a {@link StatisticalSummary} describing this distribution.
* Returns a
* {@link org.apache.commons.math.stat.univariate.StatisticalSummary}
* describing this distribution.
* <strong>Preconditions:</strong><ul>
* <li>the distribution must be loaded before invoking this method</li>
* </ul>
@ -108,9 +110,10 @@ public interface EmpiricalDistribution {
int getBinCount();
/**
* Returns a list of {@link SummaryStatistics} containing statistics
* describing the values in each of the bins. The List is indexed on
* the bin number.
* Returns a list of
* {@link org.apache.commons.math.stat.univariate.SummaryStatistics}
* containing statistics describing the values in each of the bins. The
* List is indexed on the bin number.
*
* @return List of bin statistics
*/

81
src/java/org/apache/commons/math/random/RandomDataImpl.java
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@ -25,18 +25,16 @@ import java.util.Random;
import java.util.Collection;
/**
* Implements the <code>RandomData</code> interface using
* <code>java.util.Random</code> and
* <code>java.util.Random.SecureRandom</code> instances to generate data.
* Implements the {@link RandomData} interface using
* {@link java.util.Random} and {@link java.util.Random.SecureRandom} instances
* to generate data.
* <p>
* Supports reseeding the underlying
* <a href="http://en.wikipedia.org/wiki/Pseudorandom_number_generator">
* PRNG</a>. The <code>SecurityProvider</code> and <code>Algorithm</code>
* 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>
* For details on the PRNGs, see the JDK documentation for
* <code>java.util.Random</code> and
* <code>java.util.Random.SecureRandom</code>
* For details on the PRNGs, see {@link java.util.Random} and
* {@link java.util.Random.SecureRandom}.
* <p>
* <strong>Usage Notes</strong>: <ul>
* <li>
@ -45,9 +43,13 @@ import java.util.Collection;
* to generate a random sequence of values or strings, you should use just
* <strong>one</strong> <code>RandomDataImpl</code> instance repeatedly.</li>
* <li>
* The "secure" methods are *much* slower. These should be used only when
* a <a href="http://en.wikipedia.org/wiki/Cryptographically_secure_pseudo-random_number_generator">
* Secure Random Sequence</a> is required.</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>RandomDataImpl</code> is created, the underlying random
* number generators are <strong>not</strong> intialized. The first call to a
@ -64,9 +66,12 @@ import java.util.Collection;
* 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></ul>
* identical).</li>
* <li>
* This implementation is not synchronized.
* </ul>
*
* @version $Revision: 1.15 $ $Date: 2004/06/14 23:15:15 $
* @version $Revision: 1.16 $ $Date: 2004/07/22 02:34:25 $
*/
public class RandomDataImpl implements RandomData, Serializable {
@ -133,6 +138,7 @@ public class RandomDataImpl implements RandomData, Serializable {
/**
* Generate a random int value uniformly distributed between
* <code>lower</code> and <code>upper</code>, inclusive.
*
* @param lower the lower bound.
* @param upper the upper bound.
* @return the random integer.
@ -149,6 +155,7 @@ public class RandomDataImpl implements RandomData, Serializable {
/**
* Generate a random long value uniformly distributed between
* <code>lower</code> and <code>upper</code>, inclusive.
*
* @param lower the lower bound.
* @param upper the upper bound.
* @return the random integer.
@ -171,12 +178,10 @@ public class RandomDataImpl implements RandomData, Serializable {
* <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>
* TODO: find external reference or provide justification for the claim
* that this yields a cryptographically secure sequence of hex strings.
* @param len the desired string length.
* @return the random string.
* Each byte of the binary digest is converted to 2 hex digits.</li></ol>
*
* @param len the length of the generated string
* @return the random string
*/
public String nextSecureHexString(int len) {
if (len <= 0) {
@ -229,7 +234,8 @@ public class RandomDataImpl implements RandomData, Serializable {
/**
* Generate a random int value uniformly distributed between
* <code>lower</code> and <code>upper</code>, inclusive. This algorithm
* using a secure random number generator for its engine.
* uses a secure random number generator.
*
* @param lower the lower bound.
* @param upper the upper bound.
* @return the random integer.
@ -246,7 +252,8 @@ public class RandomDataImpl implements RandomData, Serializable {
/**
* Generate a random long value uniformly distributed between
* <code>lower</code> and <code>upper</code>, inclusive. This algorithm
* using a secure random number generator for its engine.
* uses a secure random number generator.
*
* @param lower the lower bound.
* @param upper the upper bound.
* @return the random integer.
@ -261,7 +268,8 @@ public class RandomDataImpl implements RandomData, Serializable {
}
/**
* Generates a random long value from the Poisson distribution with the given mean.
* Generates a random long value from the Poisson distribution with the
* given mean.
* <p>
* <strong>Algorithm Description</strong>:
* Uses simulation of a Poisson process using Uniform deviates, as
@ -269,7 +277,9 @@ public class RandomDataImpl implements RandomData, Serializable {
* <a href ="http://dmawww.epfl.ch/benarous/Pmmi/interactive/rng7.htm">
* here.</a>
* <p>
* The Poisson process (and hence value returned) is bounded by 1000 * mean.
* The Poisson process (and hence value returned) is bounded by
* 1000 * mean.
*
* @param mean mean of the Poisson distribution.
* @return the random Poisson value.
*/
@ -295,13 +305,13 @@ public class RandomDataImpl implements RandomData, Serializable {
}
/**
* Generate a random value from a Normal distribution. This algorithm
* generates random values for the general Normal distribution with the
* given mean, <code>mu</code> and the given standard deviation,
* Generate a random value from a Normal (a.k.a. Gaussian) distribution
* with the given mean, <code>mu</code> and the given standard deviation,
* <code>sigma</code>.
* @param mu the mean of the distribution.
* @param sigma the standard deviation of the distribution.
* @return the random Normal value.
*
* @param mu the mean of the distribution
* @param sigma the standard deviation of the distribution
* @return the random Normal value
*/
public double nextGaussian(double mu, double sigma) {
if (sigma <= 0) {
@ -312,11 +322,16 @@ public class RandomDataImpl implements RandomData, Serializable {
}
/**
* Returns a random value from an Exponential distribution with the given
* mean.
* <p>
* <strong>Algorithm Description</strong>: Uses the
* <a href="http://www.jesus.ox.ac.uk/~clifford/a5/chap1/node5.html">
* Inversion Method</a> to generate exponential from uniform deviates.
* @param mean the mean of the distribution.
* @return the random Exponential value.
* Inversion Method</a> to generate exponentially distributed random values
* from uniform deviates.
*
* @param mean the mean of the distribution
* @return the random Exponential value
*/
public double nextExponential(double mean) {
if (mean < 0.0) {