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Fixed JavaDoc warnings. 

Fixed a few TODOs in the interpolation code.
Updated project TODO list.
Promoted myself to "developer".


git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140998 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Joerg Pietschmann 2003-09-26 19:30:33 +00:00
parent 2d04bb133a
commit 609917a77c
16 changed files with 140 additions and 89 deletions
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12
project.xml
View File

@ -1,5 +1,5 @@
<?xml version="1.0" encoding="UTF-8"?>
<!-- $Revision: 1.24 $ $Date: 2003/09/17 19:29:28 $ -->
<!-- $Revision: 1.25 $ $Date: 2003/09/26 19:30:32 $ -->
<project>
<extend>../../jakarta-commons/project.xml</extend>
<name>Math</name>
@ -36,6 +36,12 @@
<id>mdiggory</id>
<email>mdiggory@apache.org</email>
</developer>
<developer>
<name>J.Pietschmann</name>
<id>pietsch</id>
<email>pietsch@apache.org</email>
<email>j3322ptm@yahoo.de</email>
</developer>
</developers>
<contributors>
<contributor>
@ -54,10 +60,6 @@
<name>Albert Davidson Chou</name>
<email>hotfusionman@yahoo.com</email>
</contributor>
<contributor>
<name>J.Pietschmann</name>
<email>j3322ptm@yahoo.de</email>
</contributor>
</contributors>
<dependencies>
<dependency>

63
src/java/org/apache/commons/math/analysis/SplineInterpolator.java
View File

@ -56,7 +56,7 @@ package org.apache.commons.math.analysis;
/**
* Computes a natural spline interpolation for the data set.
*
* @version $Revision: 1.4 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.5 $ $Date: 2003/09/26 19:30:32 $
*
*/
public class SplineInterpolator implements UnivariateRealInterpolator {
@ -71,8 +71,7 @@ public class SplineInterpolator implements UnivariateRealInterpolator {
*/
public UnivariateRealFunction interpolate(double[] xval, double[] yval) {
if (xval.length != yval.length) {
throw new IllegalArgumentException(
"Dataset arrays must have same length.");
throw new IllegalArgumentException("Dataset arrays must have same length.");
}
if (c == null) {
@ -82,8 +81,7 @@ public class SplineInterpolator implements UnivariateRealInterpolator {
// Separation should be checked too (not implemented: which criteria?).
for (int i = 0; i < n; i++) {
if (xval[i] >= xval[i + 1]) {
throw new IllegalArgumentException(
"Dataset must specify sorted, ascending x values.");
throw new IllegalArgumentException("Dataset must specify sorted, ascending x values.");
}
}
// Vectors for the equation system. There are n-1 equations for the unknowns s[i] (1<=i<=N-1),
@ -95,36 +93,39 @@ public class SplineInterpolator implements UnivariateRealInterpolator {
// ...
// l[N-4]*s[N-3]+d[N-3]*s[N-2]+u[N-3]*s[N-1] = b[N-3]
// l[N-3]*s[N-2]+d[N-2]*s[N-1] = b[N-2]
// Vector b is the right hand side of the system.
// Vector b is the right hand side (RHS) of the system.
double b[] = new double[n - 1];
// Vector d is diagonal of the matrix and also holds the computed solution.
double d[] = new double[n - 1];
// u[] and l[] are not really needed, the computation can be folded into the
// system solving loops.
//double u[] = new double[n - 2]; // upper diagonal
//double l[] = new double[n - 2]; // lower diagonal
// Setup RHS and diagonal.
// Setup right hand side and diagonal.
double dquot = (yval[1] - yval[0]) / (xval[1] - xval[0]);
for (int i = 0; i < n - 1; i++) {
// TODO avoid recomputing the term
// (yval[i + 2] - yval[i + 1]) / (xval[i + 2] - xval[i + 1])
// take it from the previous loop pass. Note: the interesting part of performance
// loss is the range check in the array access, not the computation itself.
b[i] = 6.0 * ((yval[i + 2] - yval[i + 1]) / (xval[i + 2] -
xval[i + 1]) - (yval[i + 1] - yval[i]) / (xval[i + 1] -
xval[i]));
double dquotNext =
(yval[i + 2] - yval[i + 1]) / (xval[i + 2] - xval[i + 1]);
b[i] = 6.0 * (dquotNext - dquot);
d[i] = 2.0 * (xval[i + 2] - xval[i]);
dquot = dquotNext;
}
// u[] and l[] (for the upper and lower diagonal respectively) are not
// really needed, the computation is folded into the system solving loops.
// Keep this for documentation purposes:
//double u[] = new double[n - 2]; // upper diagonal
//double l[] = new double[n - 2]; // lower diagonal
// Set up upper and lower diagonal. Keep the offsets in mind.
//for (int i = 0; i < n - 2; i++) {
//u[i] = xval[i + 2] - xval[i + 1];
//l[i] = xval[i + 2] - xval[i + 1];
// u[i] = xval[i + 2] - xval[i + 1];
// l[i] = xval[i + 2] - xval[i + 1];
//}
// Solve the system: forward pass.
for (int i = 0; i < n - 2; i++) {
// TODO: This relies on compiler for CSE of delta/d[i]. Is this a reasonable assumption?
double delta = xval[i + 2] - xval[i + 1];
d[i + 1] -= delta * delta / d[i];
b[i + 1] -= b[i] * delta / d[i];
double deltaquot = delta / d[i];
d[i + 1] -= delta * deltaquot;
b[i + 1] -= b[i] * deltaquot;
}
// Solve the system: backward pass.
d[n - 2] = b[n - 2] / d[n - 2];
@ -134,23 +135,23 @@ public class SplineInterpolator implements UnivariateRealInterpolator {
// Compute coefficients as usual polynomial coefficients.
// Not the best with respect to roundoff on evaluation, but simple.
c = new double[n][4];
c[0][3] = d[0] / (xval[1] - xval[0]) / 6.0;
double delta = xval[1] - xval[0];
c[0][3] = d[0] / delta / 6.0;
c[0][2] = 0.0;
c[0][1] = (yval[1] - yval[0]) / (xval[1] - xval[0]) - d[0] *
(xval[1] - xval[0]) / 6.0;
c[0][1] = (yval[1] - yval[0]) / delta - d[0] * delta / 6.0;
for (int i = 1; i < n - 2; i++) {
// TODO: This relies on compiler for CSE of xval[i + 1] - xval[i]. Is this a reasonable assumption?
c[i][3] = (d[i] - d[i - 1]) / (xval[i + 1] - xval[i]) / 6.0;
delta = xval[i + 1] - xval[i];
c[i][3] = (d[i] - d[i - 1]) / delta / 6.0;
c[i][2] = d[i - 1] / 2.0;
c[i][1] = (yval[i + 1] - yval[i]) / (xval[i + 1] - xval[i]) -
d[i] * (xval[i + 1] - xval[i]) / 6.0 - d[i - 1] *
(xval[i + 1] - xval[i]) / 3.0;
c[i][1] =
(yval[i + 1] - yval[i]) / delta
- (d[i] / 2.0 - d[i - 1]) * delta / 3.0;
}
// TODO: again, CSE aspects.
c[n - 1][3] = -d[n - 2] / (xval[n] - xval[n - 1]) / 6.0;
delta = (xval[n] - xval[n - 1]);
c[n - 1][3] = -d[n - 2] / delta / 6.0;
c[n - 1][2] = d[n - 2] / 2.0;
c[n - 1][1] = (yval[n] - yval[n - 1]) / (xval[n] - xval[n - 1]) -
d[n - 2] * (xval[n] - xval[n - 1]) / 3.0;
c[n - 1][1] =
(yval[n] - yval[n - 1]) / delta - d[n - 2] * delta / 3.0;
for (int i = 0; i < n; i++) {
c[i][0] = yval[i];
}

6
src/java/org/apache/commons/math/distribution/AbstractDiscreteDistribution.java
View File

@ -59,7 +59,7 @@ package org.apache.commons.math.stat.distribution;
* implementations for some of the methods that do not vary from distribution
* to distribution.
*
* @version $Revision: 1.1 $ $Date: 2003/08/16 17:06:15 $
* @version $Revision: 1.2 $ $Date: 2003/09/26 19:30:33 $
*/
public abstract class AbstractDiscreteDistribution
implements DiscreteDistribution {
@ -139,7 +139,7 @@ public abstract class AbstractDiscreteDistribution
/**
* Access the domain value lower bound, based on <code>p</code>, used to
* bracket a PDF root. This method is used by
* {@link #inverseCummulativeProbability(int)} to find critical values.
* {@link #inverseCummulativeProbability(double)} to find critical values.
*
* @param p the desired probability for the critical value
* @return domain value lower bound, i.e.
@ -150,7 +150,7 @@ public abstract class AbstractDiscreteDistribution
/**
* Access the domain value upper bound, based on <code>p</code>, used to
* bracket a PDF root. This method is used by
* {@link #inverseCummulativeProbability(int)} to find critical values.
* {@link #inverseCummulativeProbability(double)} to find critical values.
*
* @param p the desired probability for the critical value
* @return domain value upper bound, i.e.

11
src/java/org/apache/commons/math/distribution/GammaDistributionImpl.java
View File

@ -58,7 +58,7 @@ import org.apache.commons.math.special.Gamma;
/**
* The default implementation of {@link GammaDistribution}
*
* @version $Revision: 1.6 $ $Date: 2003/09/17 19:29:28 $
* @version $Revision: 1.7 $ $Date: 2003/09/26 19:30:33 $
*/
public class GammaDistributionImpl extends AbstractContinuousDistribution
implements GammaDistribution {
@ -153,7 +153,7 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
* @param p the desired probability for the critical value
* @return domain value lower bound, i.e.
* P(X &lt; <i>lower bound</i>) &lt; <code>p</code>
* @todo try to improve on this estimate
* TODO: try to improve on this estimate
*/
protected double getDomainLowerBound(double p) {
return Double.MIN_VALUE;
@ -167,7 +167,7 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
* @param p the desired probability for the critical value
* @return domain value upper bound, i.e.
* P(X &lt; <i>upper bound</i>) &gt; <code>p</code>
* @todo try to improve on this estimate
* TODO: try to improve on this estimate
*/
protected double getDomainUpperBound(double p) {
// NOTE: gamma is skewed to the left
@ -193,11 +193,10 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
*
* @param p the desired probability for the critical value
* @return initial domain value
* @todo try to improve on this estimate
* TODO: try to improve on this estimate
*/
protected double getInitialDomain(double p) {
// NOTE: gamma is skewed to the left
// NOTE: therefore, P(X < &mu;) > .5
// Gamma is skewed to the left, therefore, P(X < &mu;) > .5
double ret;

4
src/java/org/apache/commons/math/stat/AbstractStoreUnivariate.java
View File

@ -59,7 +59,7 @@ import org.apache.commons.math.stat.univariate.rank.Percentile;
/**
* Provides univariate measures for an array of doubles.
* @version $Revision: 1.10 $ $Date: 2003/07/15 03:45:10 $
* @version $Revision: 1.11 $ $Date: 2003/09/26 19:30:32 $
*/
public abstract class AbstractStoreUnivariate
extends AbstractUnivariate
@ -92,7 +92,7 @@ public abstract class AbstractStoreUnivariate
}
/**
* @see org.apache.commons.math.stat2.AbstractStoreUnivariate#getSortedValues()
* @see org.apache.commons.math.stat.StoreUnivariate#getSortedValues()
*/
public double[] getSortedValues() {
double[] sort = getValues();

8
src/java/org/apache/commons/math/stat/AbstractUnivariate.java
View File

@ -68,7 +68,7 @@ import org.apache.commons.math.stat.univariate.summary.SumOfSquares;
/**
* Provides univariate measures for an array of doubles.
* @version $Revision: 1.2 $ $Date: 2003/07/15 03:45:10 $
* @version $Revision: 1.3 $ $Date: 2003/09/26 19:30:32 $
*/
public abstract class AbstractUnivariate implements Univariate {
@ -294,7 +294,7 @@ public abstract class AbstractUnivariate implements Univariate {
}
/**
* @see org.apache.commons.math.Univariate#clear()
* @see org.apache.commons.math.stat.Univariate#clear()
*/
public void clear() {
this.n = 0;
@ -313,14 +313,14 @@ public abstract class AbstractUnivariate implements Univariate {
}
/**
* @see org.apache.commons.math.Univariate#getWindowSize()
* @see org.apache.commons.math.stat.Univariate#getWindowSize()
*/
public int getWindowSize() {
return windowSize;
}
/**
* @see org.apache.commons.math.Univariate#setWindowSize(int)
* @see org.apache.commons.math.stat.Univariate#setWindowSize(int)
*/
public void setWindowSize(int windowSize) {
clear();

56
src/java/org/apache/commons/math/stat/Applyable.java
View File

@ -1,6 +1,55 @@
/*
* Created on Jul 15, 2003
/* ====================================================================
* The Apache Software License, Version 1.1
*
* Copyright (c) 2003 The Apache Software Foundation. All rights
* reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* 3. The end-user documentation included with the redistribution, if
* any, must include the following acknowlegement:
* "This product includes software developed by the
* Apache Software Foundation (http://www.apache.org/)."
* Alternately, this acknowlegement may appear in the software itself,
* if and wherever such third-party acknowlegements normally appear.
*
* 4. The names "The Jakarta Project", "Commons", and "Apache Software
* Foundation" must not be used to endorse or promote products derived
* from this software without prior written permission. For written
* permission, please contact apache@apache.org.
*
* 5. Products derived from this software may not be called "Apache"
* nor may "Apache" appear in their names without prior written
* permission of the Apache Software Foundation.
*
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
* ====================================================================
*
* This software consists of voluntary contributions made by many
* individuals on behalf of the Apache Software Foundation. For more
* information on the Apache Software Foundation, please see
* <http://www.apache.org/>.
*/
package org.apache.commons.math.stat;
@ -9,8 +58,7 @@ import org.apache.commons.math.stat.univariate.UnivariateStatistic;
/**
* Applyable.java
*
* To change the template for this generated type comment go to
* Window>Preferences>Java>Code Generation>Code and Comments
* TODO: add javadocs
*
*/
public interface Applyable {

4
src/java/org/apache/commons/math/stat/BeanListUnivariateImpl.java
View File

@ -62,7 +62,7 @@ import org.apache.commons.math.util.BeanTransformer;
* univariate statistics for a List of Java Beans by property. This
* implementation uses beanutils' PropertyUtils to get a simple, nested,
* indexed, mapped, or combined property from an element of a List.
* @version $Revision: 1.5 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.6 $ $Date: 2003/09/26 19:30:32 $
*/
public class BeanListUnivariateImpl extends ListUnivariateImpl {
@ -109,7 +109,7 @@ public class BeanListUnivariateImpl extends ListUnivariateImpl {
}
/**
* @see org.apache.commons.math.Univariate#addValue(double)
* @see org.apache.commons.math.stat.Univariate#addValue(double)
*/
public void addValue(double v) {
String msg =

12
src/java/org/apache/commons/math/stat/ListUnivariateImpl.java
View File

@ -60,7 +60,7 @@ import org.apache.commons.math.util.DefaultTransformer;
import org.apache.commons.math.util.NumberTransformer;
/**
* @version $Revision: 1.5 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.6 $ $Date: 2003/09/26 19:30:32 $
*/
public class ListUnivariateImpl
extends AbstractStoreUnivariate
@ -97,7 +97,7 @@ public class ListUnivariateImpl
}
/**
* @see org.apache.commons.math.StoreUnivariate#getValues()
* @see org.apache.commons.math.stat.StoreUnivariate#getValues()
*/
public double[] getValues() {
@ -124,7 +124,7 @@ public class ListUnivariateImpl
}
/**
* @see org.apache.commons.math.StoreUnivariate#getElement(int)
* @see org.apache.commons.math.stat.StoreUnivariate#getElement(int)
*/
public double getElement(int index) {
@ -148,7 +148,7 @@ public class ListUnivariateImpl
}
/**
* @see org.apache.commons.math.Univariate#getN()
* @see org.apache.commons.math.stat.Univariate#getN()
*/
public int getN() {
int n = 0;
@ -166,7 +166,7 @@ public class ListUnivariateImpl
}
/**
* @see org.apache.commons.math.Univariate#addValue(double)
* @see org.apache.commons.math.stat.Univariate#addValue(double)
*/
public void addValue(double v) {
list.add(new Double(v));
@ -181,7 +181,7 @@ public class ListUnivariateImpl
}
/**
* @see org.apache.commons.math.Univariate#clear()
* @see org.apache.commons.math.stat.Univariate#clear()
*/
public void clear() {
super.clear();

14
src/java/org/apache/commons/math/stat/StoreUnivariateImpl.java
View File

@ -57,7 +57,7 @@ import org.apache.commons.math.stat.univariate.UnivariateStatistic;
import org.apache.commons.math.util.ContractableDoubleArray;
/**
* @version $Revision: 1.6 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.7 $ $Date: 2003/09/26 19:30:32 $
*/
public class StoreUnivariateImpl extends AbstractStoreUnivariate {
@ -74,7 +74,7 @@ public class StoreUnivariateImpl extends AbstractStoreUnivariate {
}
/**
* @see org.apache.commons.math.StoreUnivariate#getValues()
* @see org.apache.commons.math.stat.StoreUnivariate#getValues()
*/
public double[] getValues() {
@ -89,21 +89,21 @@ public class StoreUnivariateImpl extends AbstractStoreUnivariate {
}
/**
* @see org.apache.commons.math.StoreUnivariate#getElement(int)
* @see org.apache.commons.math.stat.StoreUnivariate#getElement(int)
*/
public double getElement(int index) {
return eDA.getElement(index);
}
/**
* @see org.apache.commons.math.Univariate#getN()
* @see org.apache.commons.math.stat.Univariate#getN()
*/
public int getN() {
return eDA.getNumElements();
}
/**
* @see org.apache.commons.math.Univariate#addValue(double)
* @see org.apache.commons.math.stat.Univariate#addValue(double)
*/
public synchronized void addValue(double v) {
if (windowSize != Univariate.INFINITE_WINDOW) {
@ -123,7 +123,7 @@ public class StoreUnivariateImpl extends AbstractStoreUnivariate {
}
/**
* @see org.apache.commons.math.Univariate#clear()
* @see org.apache.commons.math.stat.Univariate#clear()
*/
public synchronized void clear() {
super.clear();
@ -131,7 +131,7 @@ public class StoreUnivariateImpl extends AbstractStoreUnivariate {
}
/**
* @see org.apache.commons.math.Univariate#setWindowSize(int)
* @see org.apache.commons.math.stat.Univariate#setWindowSize(int)
*/
public synchronized void setWindowSize(int windowSize) {
this.windowSize = windowSize;

4
src/java/org/apache/commons/math/stat/UnivariateImpl.java
View File

@ -67,7 +67,7 @@ import org.apache.commons.math.util.FixedDoubleArray;
* Integers, floats and longs can be added, but they will be converted
* to doubles by addValue().
*
* @version $Revision: 1.19 $ $Date: 2003/07/15 03:45:10 $
* @version $Revision: 1.20 $ $Date: 2003/09/26 19:30:32 $
*/
public class UnivariateImpl
extends AbstractUnivariate
@ -152,7 +152,7 @@ public class UnivariateImpl
}
/**
* @see org.apache.commons.math.Univariate#clear()
* @see org.apache.commons.math.stat.Univariate#clear()
*/
public void clear() {
super.clear();

6
src/java/org/apache/commons/math/util/ContractableDoubleArray.java
View File

@ -88,7 +88,7 @@ import java.io.Serializable;
* internal storage array is swapped.
* </p>
*
* @version $Revision: 1.4 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.5 $ $Date: 2003/09/26 19:30:33 $
*/
public class ContractableDoubleArray
extends ExpandableDoubleArray
@ -246,7 +246,7 @@ public class ContractableDoubleArray
* must validate the combination of expansionFactor and
* contractionCriteria.
*
* @see org.apache.commons.math.ExpandableDoubleArray#setExpansionFactor(float)
* @see org.apache.commons.math.util.ExpandableDoubleArray#setExpansionFactor(float)
*/
public void setExpansionFactor(float expansionFactor) {
checkContractExpand(getContractionCriteria(), expansionFactor);
@ -318,7 +318,7 @@ public class ContractableDoubleArray
}
/**
* @see org.apache.commons.math.ExpandableDoubleArray#discardFrontElements(int)
* @see org.apache.commons.math.util.ExpandableDoubleArray#discardFrontElements(int)
*/
public synchronized void discardFrontElements(int i) {
super.discardFrontElements(i);

4
src/java/org/apache/commons/math/util/ExpandableDoubleArray.java
View File

@ -88,7 +88,7 @@ import java.io.Serializable;
* expand the array 10 times - first from 2 -> 4. then 4 -> 8, 8 -> 16,
* and so on until we reach 4096 which is sufficient to hold 3546 elements.
* </p>
* @version $Revision: 1.5 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.6 $ $Date: 2003/09/26 19:30:33 $
*/
public class ExpandableDoubleArray implements Serializable, DoubleArray {
@ -415,7 +415,7 @@ public class ExpandableDoubleArray implements Serializable, DoubleArray {
}
/**
* @see org.apache.commons.math.DoubleArray#getElements()
* @see org.apache.commons.math.util.DoubleArray#getElements()
*/
public double[] getElements() {
double[] elementArray = new double[numElements];

14
src/java/org/apache/commons/math/util/FixedDoubleArray.java
View File

@ -82,7 +82,7 @@ package org.apache.commons.math.util;
* "fixed" in memory, this implementation will never allocate, or copy
* the internal storage array to a new array instance.
* </p>
* @version $Revision: 1.6 $ $Date: 2003/09/07 03:12:56 $
* @version $Revision: 1.7 $ $Date: 2003/09/26 19:30:33 $
*/
public class FixedDoubleArray implements DoubleArray {
@ -144,7 +144,7 @@ public class FixedDoubleArray implements DoubleArray {
/**
* Retrieves the current size of the array.
* @see org.apache.commons.math.DoubleArray#getNumElements()
* @see org.apache.commons.math.util.DoubleArray#getNumElements()
*/
public int getNumElements() {
return size;
@ -159,7 +159,7 @@ public class FixedDoubleArray implements DoubleArray {
* 2 - trying to retrieve an element outside of the current element
* array will throw an ArrayIndexOutOfBoundsException.
*
* @see org.apache.commons.math.DoubleArray#getElement(int)
* @see org.apache.commons.math.util.DoubleArray#getElement(int)
*/
public double getElement(int index) {
if (index > (size - 1)) {
@ -198,7 +198,7 @@ public class FixedDoubleArray implements DoubleArray {
* </ul>
* </p>
*
* @see org.apache.commons.math.DoubleArray#setElement(int, double)
* @see org.apache.commons.math.util.DoubleArray#setElement(int, double)
*/
public void setElement(int index, double value) {
if (index > (size - 1)) {
@ -215,7 +215,7 @@ public class FixedDoubleArray implements DoubleArray {
* this array has already met or exceeded the maximum number
* of elements
*
* @see org.apache.commons.math.DoubleArray#addElement(double)
* @see org.apache.commons.math.util.DoubleArray#addElement(double)
*/
public void addElement(double value) {
if (size < internalArray.length) {
@ -305,7 +305,7 @@ public class FixedDoubleArray implements DoubleArray {
*
* @return The array of elements added to this DoubleArray
* implementation.
* @see org.apache.commons.math.DoubleArray#getElements()
* @see org.apache.commons.math.util.DoubleArray#getElements()
*/
public double[] getElements() {
double[] copy = new double[size];
@ -336,7 +336,7 @@ public class FixedDoubleArray implements DoubleArray {
* setting the size of the array back to zero, and reinitializing
* the internal storage array.
*
* @see org.apache.commons.math.DoubleArray#clear()
* @see org.apache.commons.math.util.DoubleArray#clear()
*/
public void clear() {
size = 0;

4
src/test/org/apache/commons/math/random/RandomDataTest.java
View File

@ -14,7 +14,7 @@
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
* distribution.
*
* 3. The end-user documentation included with the redistribution, if
* any, must include the following acknowlegement:
@ -68,7 +68,7 @@ import org.apache.commons.math.stat.UnivariateImpl;
/**
* Test cases for the RandomData class.
*
* @version $Revision: 1.2 $ $Date: 2003/07/07 23:19:21 $
* @version $Revision: 1.3 $ $Date: 2003/09/26 19:30:33 $
*/
public final class RandomDataTest extends TestCase {

7
xdocs/tasks.xml
View File

@ -1,5 +1,5 @@
<?xml version="1.0"?>
<!-- $Revision: 1.8 $ $Date: 2003/09/24 20:15:50 $ -->
<!-- $Revision: 1.9 $ $Date: 2003/09/26 19:30:33 $ -->
<document>
<properties>
<title>Tasks: Done And To Do</title>
@ -40,8 +40,7 @@
<dt>Analysis.</dt>
<dd>
<ul>
<li>Framework and implementation strategie(s) for finding roots or real-valued functions of one (real) variable.</li>
<li>Cubic spline interpolation.</li>
<li>Rework unit tests for root finding and spline interpolation.</li>
<li>CheckStyle with modified properties still shows many errors. Try to clean these up.</li>
</ul>
</dd>
@ -62,6 +61,8 @@
<section name="Completed">
<subsection name="Since Conception">
<ul>
<li>Framework and implementation strategie(s) for finding roots or real-valued functions of one (real) variable. Implemented algorithms: Brent-Dekker, secant, simple bisection.</li>
<li>Cubic spline interpolation.</li>
<li>Bivariate Regression, correlation. </li>
<li>Sampling from Collections</li>
<li>Add higher order moments to Univariate implementations.</li>