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Merged changes in MATH_1_1 branch to trunk. This includes revision 232577 through revision 234481. 

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@239294 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden 2005-08-23 02:27:17 +00:00
parent 71fb92ebd4
commit fd07147f86
13 changed files with 328 additions and 120 deletions
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55
src/java/org/apache/commons/math/complex/Complex.java
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@ -66,7 +66,19 @@ public class Complex implements Serializable {
if (isNaN()) {
return Double.NaN;
}
return Math.sqrt(squareSum());
if (Math.abs(real) < Math.abs(imaginary)) {
if (imaginary == 0.0) {
return Math.abs(real);
}
double q = real / imaginary;
return (Math.abs(imaginary) * Math.sqrt(1 + q*q));
} else {
if (real == 0.0) {
return Math.abs(imaginary);
}
double q = imaginary / real;
return (Math.abs(real) * Math.sqrt(1 + q*q));
}
}
/**
@ -108,17 +120,29 @@ public class Complex implements Serializable {
if (isNaN() || rhs.isNaN()) {
return NaN;
}
if (Math.abs(rhs.getReal()) < Math.abs(rhs.getImaginary())) {
double q = rhs.getReal() / rhs.getImaginary();
double d = (rhs.getReal() * q) + rhs.getImaginary();
return new Complex(((real * q) + imaginary) / d,
((imaginary * q) - real) / d);
double c = rhs.getReal();
double d = rhs.getImaginary();
if (c == 0.0 && d == 0.0) {
throw new ArithmeticException("Error: division by zero.");
}
if (Math.abs(c) < Math.abs(d)) {
if (d == 0.0) {
return new Complex(real/c, imaginary/c);
}
double q = c / d;
double denominator = c * q + d;
return new Complex((real * q + imaginary) / denominator,
(imaginary * q - real) / denominator);
} else {
double q = rhs.getImaginary() / rhs.getReal();
double d = (rhs.getImaginary() * q) + rhs.getReal();
return new Complex(((imaginary * q) + real) / d,
(imaginary - (real * q)) / d);
if (c == 0.0) {
return new Complex(imaginary/d, -real/c);
}
double q = d / c;
double denominator = d * q + c;
return new Complex((imaginary * q + real) / denominator,
(imaginary - real * q) / denominator);
}
}
@ -215,15 +239,6 @@ public class Complex implements Serializable {
return new Complex(-real, -imaginary);
}
/**
* Return the sum of the squared terms.
*
* @return the square sum.
*/
private double squareSum() {
return real * real + imaginary * imaginary;
}
/**
* Return the difference between this complex number and the given complex
* number.

93
src/java/org/apache/commons/math/distribution/HypergeometricDistributionImpl.java
View File

@ -18,7 +18,6 @@ package org.apache.commons.math.distribution;
import java.io.Serializable;
import org.apache.commons.math.MathException;
import org.apache.commons.math.util.MathUtils;
/**
@ -54,7 +53,8 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
super();
if (numberOfSuccesses > populationSize) {
throw new IllegalArgumentException(
"number of successes must be less than or equal to population size");
"number of successes must be less than or equal to " +
"population size");
}
if (sampleSize > populationSize) {
throw new IllegalArgumentException(
@ -69,10 +69,8 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
* For this disbution, X, this method returns P(X &le; x).
* @param x the value at which the PDF is evaluated.
* @return PDF for this distribution.
* @throws MathException if the cumulative probability can not be
* computed due to convergence or other numerical errors.
*/
public double cumulativeProbability(int x) throws MathException{
public double cumulativeProbability(int x) {
double ret;
int n = getPopulationSize();
@ -84,11 +82,10 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
ret = 0.0;
} else if(x >= domain[1]) {
ret = 1.0;
} else if (x - domain[0] < domain[1] - x) {
ret = lowerCumulativeProbability(domain[0], x, n, m, k);
} else {
ret = 0.0;
for (int i = domain[0]; i <= x; ++i){
ret += probability(n, m, k, i);
}
ret = 1.0 - upperCumulativeProbability(x + 1, domain[1], n, m, k);
}
return ret;
@ -181,6 +178,28 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
return Math.min(k, m);
}
/**
* For this disbution, X, this method returns P(x0 &le; X &le; x1). This
* probability is computed by summing the point probabilities for the values
* x0, x0 + 1, x0 + 2, ..., x1, in that order.
* @param x0 the inclusive, lower bound
* @param x1 the inclusive, upper bound
* @param n the population size.
* @param m number of successes in the population.
* @param k the sample size.
* @return P(x0 &le; X &le; x1).
*/
private double lowerCumulativeProbability(
int x0, int x1, int n, int m, int k)
{
double ret;
ret = 0.0;
for (int i = x0; i <= x1; ++i) {
ret += probability(n, m, k, i);
}
return ret;
}
/**
* For this disbution, X, this method returns P(X = x).
*
@ -203,7 +222,7 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
return ret;
}
/**
* For the disbution, X, defined by the given hypergeometric distribution
* parameters, this method returns P(X = x).
@ -219,7 +238,7 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
MathUtils.binomialCoefficientLog(n - m, k - x) -
MathUtils.binomialCoefficientLog(n, k));
}
/**
* Modify the number of successes.
* @param num the new number of successes.
@ -245,8 +264,8 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
}
populationSize = size;
}
/**
/**
* Modify the sample size.
* @param size the new sample size.
* @throws IllegalArgumentException if <code>size</code> is negative.
@ -258,4 +277,52 @@ public class HypergeometricDistributionImpl extends AbstractIntegerDistribution
}
sampleSize = size;
}
/**
* For this disbution, X, this method returns P(X &ge; x).
* @param x the value at which the CDF is evaluated.
* @return upper tail CDF for this distribution.
*/
public double upperCumulativeProbability(int x) {
double ret;
int n = getPopulationSize();
int m = getNumberOfSuccesses();
int k = getSampleSize();
int[] domain = getDomain(n, m, k);
if (x < domain[0]) {
ret = 1.0;
} else if(x >= domain[1]) {
ret = 0.0;
} else if (x - domain[0] < domain[1] - x) {
ret = 1.0 - lowerCumulativeProbability(domain[0], x - 1, n, m, k);
} else {
ret = upperCumulativeProbability(x, domain[1], n, m, k);
}
return ret;
}
/**
* For this disbution, X, this method returns P(x0 &le; X &le; x1). This
* probability is computed by summing the point probabilities for the values
* x1, x1 - 1, x1 - 2, ..., x0, in that order.
* @param x0 the inclusive, lower bound
* @param x1 the inclusive, upper bound
* @param n the population size.
* @param m number of successes in the population.
* @param k the sample size.
* @return P(x0 &le; X &le; x1).
*/
private double upperCumulativeProbability(
int x0, int x1, int n, int m, int k)
{
double ret = 0.0;
for (int i = x1; i >= x0; --i) {
ret += probability(n, m, k, i);
}
return ret;
}
}

4
src/java/org/apache/commons/math/special/Gamma.java
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@ -155,7 +155,7 @@ public class Gamma implements Serializable {
ret = Double.NaN;
} else if (x == 0.0) {
ret = 0.0;
} else if (a > 1.0 && x > a) {
} else if (a >= 1.0 && x > a) {
// use regularizedGammaQ because it should converge faster in this
// case.
ret = 1.0 - regularizedGammaQ(a, x, epsilon, maxIterations);
@ -231,7 +231,7 @@ public class Gamma implements Serializable {
ret = Double.NaN;
} else if (x == 0.0) {
ret = 1.0;
} else if (x < a || a <= 1.0) {
} else if (x < a || a < 1.0) {
// use regularizedGammaP because it should converge faster in this
// case.
ret = 1.0 - regularizedGammaP(a, x, epsilon, maxIterations);

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

@ -604,8 +604,8 @@ public final class StatUtils {
double sum2 = 0d;
double diff = 0d;
int n = sample1.length;
if (n < 2) {
throw new IllegalArgumentException("Input array lengths must be at least 2.");
if (n < 2 || n != sample2.length) {
throw new IllegalArgumentException("Input array lengths must be equal and at least 2.");
}
for (int i = 0; i < n; i++) {
diff = sample1[i] - sample2[i];

127
src/java/org/apache/commons/math/util/ContinuedFraction.java
View File

@ -100,16 +100,25 @@ public abstract class ContinuedFraction implements Serializable {
}
/**
* <p>
* Evaluates the continued fraction at the value x.
* </p>
*
* The implementation of this method is based on:
* <p>
* The implementation of this method is based on equations 14-17 of:
* <ul>
* <li>O. E-gecio-glu, C . K. Koc, J. Rifa i Coma,
* <a href="http://citeseer.ist.psu.edu/egecioglu91fast.html">
* On Fast Computation of Continued Fractions</a>, Computers Math. Applic.,
* 21(2--3), 1991, 167--169.</li>
* <li>
* Eric W. Weisstein. "Continued Fraction." From MathWorld--A Wolfram Web
* Resource. <a target="_blank"
* href="http://mathworld.wolfram.com/ContinuedFraction.html">
* http://mathworld.wolfram.com/ContinuedFraction.html</a>
* </li>
* </ul>
*
* The recurrence relationship defined in those equations can result in
* very large intermediate results which can result in numerical overflow.
* As a means to combat these overflow conditions, the intermediate results
* are scaled whenever they threaten to become numerically unstable.
*
* @param x the evaluation point.
* @param epsilon maximum error allowed.
* @param maxIterations maximum number of convergents
@ -119,72 +128,50 @@ public abstract class ContinuedFraction implements Serializable {
public double evaluate(double x, double epsilon, int maxIterations)
throws MathException
{
double[][] f = new double[2][2];
double[][] a = new double[2][2];
double[][] an = new double[2][2];
double p0 = 1.0;
double p1 = getA(0, x);
double q0 = 0.0;
double q1 = 1.0;
double c = p1 / q1;
int n = 0;
double relativeError = Double.MAX_VALUE;
while (n < maxIterations && relativeError > epsilon) {
++n;
double a = getA(n, x);
double b = getB(n, x);
double p2 = a * p1 + b * p0;
double q2 = a * q1 + b * q0;
if (Double.isInfinite(p2) || Double.isInfinite(q2)) {
// need to scale
if (a != 0.0) {
p2 = p1 + (b / a * p0);
q2 = q1 + (b / a * q0);
} else if (b != 0) {
p2 = (a / b * p1) + p0;
q2 = (a / b * q1) + q0;
} else {
// can not scale an convergent is unbounded.
throw new ConvergenceException(
"Continued fraction convergents diverged to +/- " +
"infinity.");
}
}
double r = p2 / q2;
relativeError = Math.abs(r / c - 1.0);
// prepare for next iteration
c = p2 / q2;
p0 = p1;
p1 = p2;
q0 = q1;
q1 = q2;
}
a[0][0] = getA(0, x);
a[0][1] = 1.0;
a[1][0] = 1.0;
a[1][1] = 0.0;
return evaluate(1, x, a, an, f, epsilon, maxIterations);
}
/**
* Evaluates the n-th convergent, fn = pn / qn, for this continued fraction
* at the value x.
* @param n the convergent to compute.
* @param x the evaluation point.
* @param a (n-1)-th convergent matrix. (Input)
* @param an the n-th coefficient matrix. (Output)
* @param f the n-th convergent matrix. (Output)
* @param epsilon maximum error allowed.
* @param maxIterations maximum number of convergents
* @return the value of the the n-th convergent for this continued fraction
* evaluated at x.
* @throws MathException if the algorithm fails to converge.
*/
private double evaluate(
int n,
double x,
double[][] a,
double[][] an,
double[][] f,
double epsilon,
int maxIterations) throws MathException
{
double ret;
// create next matrix
an[0][0] = getA(n, x);
an[0][1] = 1.0;
an[1][0] = getB(n, x);
an[1][1] = 0.0;
// multiply a and an, save as f
f[0][0] = (a[0][0] * an[0][0]) + (a[0][1] * an[1][0]);
f[0][1] = (a[0][0] * an[0][1]) + (a[0][1] * an[1][1]);
f[1][0] = (a[1][0] * an[0][0]) + (a[1][1] * an[1][0]);
f[1][1] = (a[1][0] * an[0][1]) + (a[1][1] * an[1][1]);
// determine if we're close enough
if (Math.abs((f[0][0] * f[1][1]) - (f[1][0] * f[0][1])) <
Math.abs(epsilon * f[1][0] * f[1][1]))
{
ret = f[0][0] / f[1][0];
} else {
if (n >= maxIterations) {
throw new ConvergenceException(
"Continued fraction convergents failed to converge.");
}
// compute next
ret = evaluate(n + 1, x, f /* new a */
, an /* reuse an */
, a /* new f */
, epsilon, maxIterations);
if (n >= maxIterations) {
throw new ConvergenceException(
"Continued fraction convergents failed to converge.");
}
return ret;
return c;
}
}

29
src/java/org/apache/commons/math/util/MathUtils.java
View File

@ -1,12 +1,17 @@
/*
* Copyright 2003-2005 The Apache Software Foundation. Licensed 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.
* Copyright 2003-2004 The Apache Software Foundation.
*
* Licensed 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.math.util;
@ -15,9 +20,7 @@ import java.math.BigDecimal;
/**
* Some useful additions to the built-in functions in {@link Math}.
*
* @version $Revision$ $Date: 2005-07-30 02:25:26 -0500 (Sat, 30 Jul
* 2005) $
* @version $Revision$ $Date$
*/
public final class MathUtils {
@ -496,7 +499,7 @@ public final class MathUtils {
* @since 1.1
*/
public static double round(double x, int scale, int roundingMethod) {
double sign = sign(x);
double sign = indicator(x);
double factor = Math.pow(10.0, scale) * sign;
return roundUnscaled(x * factor, sign, roundingMethod) / factor;
}
@ -527,7 +530,7 @@ public final class MathUtils {
* @since 1.1
*/
public static float round(float x, int scale, int roundingMethod) {
float sign = sign(x);
float sign = indicator(x);
float factor = (float)Math.pow(10.0f, scale) * sign;
return (float)roundUnscaled(x * factor, sign, roundingMethod) / factor;
}

44
src/test/org/apache/commons/math/distribution/PoissonDistributionTest.java
View File

@ -15,6 +15,8 @@
*/
package org.apache.commons.math.distribution;
import org.apache.commons.math.MathException;
/**
* <code>PoissonDistributionTest</code>
*
@ -133,4 +135,46 @@ public class PoissonDistributionTest extends IntegerDistributionAbstractTest {
dist.setMean(10.0);
assertEquals(10.0, dist.getMean(), 0.0);
}
public void testLargeMeanCumulativeProbability() {
PoissonDistribution dist = DistributionFactory.newInstance().createPoissonDistribution(1.0);
double mean = 1.0;
while (mean <= 10000000.0) {
dist.setMean(mean);
double x = mean * 2.0;
double dx = x / 10.0;
while (x >= 0) {
try {
dist.cumulativeProbability(x);
} catch (MathException ex) {
fail("mean of " + mean + " and x of " + x + " caused " + ex.getMessage());
}
x -= dx;
}
mean *= 10.0;
}
}
public void testLargeMeanInverseCumulativeProbability() {
PoissonDistribution dist = DistributionFactory.newInstance().createPoissonDistribution(1.0);
double mean = 1.0;
while (mean <= 10000000.0) {
dist.setMean(mean);
double p = 0.1;
double dp = p;
while (p < 1.0) {
try {
dist.inverseCumulativeProbability(p);
} catch (MathException ex) {
fail("mean of " + mean + " and p of " + p + " caused " + ex.getMessage());
}
p += dp;
}
mean *= 10.0;
}
}
}

18
src/test/org/apache/commons/math/linear/RealMatrixImplTest.java
View File

@ -422,6 +422,11 @@ public final class RealMatrixImplTest extends TestCase {
RealMatrix lu = m.getLUMatrix();
assertClose("LU decomposition", lu, (RealMatrix) new RealMatrixImpl(testDataLU), normTolerance);
verifyDecomposition(m, lu);
// access LU decomposition on same object to verify caching.
lu = m.getLUMatrix();
assertClose("LU decomposition", lu, (RealMatrix) new RealMatrixImpl(testDataLU), normTolerance);
verifyDecomposition(m, lu);
m = new RealMatrixImpl(luData);
lu = m.getLUMatrix();
assertClose("LU decomposition", lu, (RealMatrix) new RealMatrixImpl(luDataLUDecomposition), normTolerance);
@ -642,6 +647,19 @@ public final class RealMatrixImplTest extends TestCase {
} catch (MatrixIndexException e) {
// expected
}
// dimension underflow
try {
m.setSubMatrix(testData,-1,1);
fail("expecting MatrixIndexException");
} catch (MatrixIndexException e) {
// expected
}
try {
m.setSubMatrix(testData,1,-1);
fail("expecting MatrixIndexException");
} catch (MatrixIndexException e) {
// expected
}
// null
try {

17
src/test/org/apache/commons/math/stat/FrequencyTest.java
View File

@ -20,6 +20,8 @@ import java.io.IOException;
import java.io.StringReader;
import java.util.Iterator;
import org.apache.commons.math.TestUtils;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
@ -111,6 +113,21 @@ public final class FrequencyTest extends TestCase {
assertEquals("one count", 3 , f.getCount("one"));
assertEquals("Z cumulative pct -- case insensitive", 1 , f.getCumPct("Z"), tolerance);
assertEquals("z cumulative pct -- case insensitive", 1 , f.getCumPct("z"), tolerance);
f = null;
f = new Frequency();
assertEquals(0L, f.getCount('a'));
assertEquals(0L, f.getCumFreq('b'));
TestUtils.assertEquals(Double.NaN, f.getPct('a'), 0.0);
TestUtils.assertEquals(Double.NaN, f.getCumPct('b'), 0.0);
f.addValue('a');
f.addValue('b');
f.addValue('c');
f.addValue('d');
assertEquals(1L, f.getCount('a'));
assertEquals(2L, f.getCumFreq('b'));
assertEquals(0.25, f.getPct('a'), 0.0);
assertEquals(0.5, f.getCumPct('b'), 0.0);
}
/** test pcts */

15
src/test/org/apache/commons/math/stat/StatUtilsTest.java
View File

@ -371,6 +371,19 @@ public final class StatUtilsTest extends TestCase {
} catch (IllegalArgumentException ex) {
// expected
}
try {
StatUtils.varianceDifference(sample1, small, meanDifference);
fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// expected
}
try {
double[] single = {1.0};
StatUtils.varianceDifference(single, single, meanDifference);
fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// expected
}
}
public void testGeometricMean() throws Exception {
@ -384,5 +397,7 @@ public final class StatUtilsTest extends TestCase {
test = new double[] {2, 4, 6, 8};
assertEquals(Math.exp(0.25d * StatUtils.sumLog(test)),
StatUtils.geometricMean(test), Double.MIN_VALUE);
assertEquals(Math.exp(0.5 * StatUtils.sumLog(test, 0, 2)),
StatUtils.geometricMean(test, 0, 2), Double.MIN_VALUE);
}
}

14
src/test/org/apache/commons/math/stat/descriptive/rank/PercentileTest.java
View File

@ -72,6 +72,20 @@ public class PercentileTest extends UnivariateStatisticAbstractTest{
assertEquals(3.75, p.evaluate(d), 1.0e-5);
p.setQuantile(50);
assertEquals(2.5, p.evaluate(d), 1.0e-5);
// invalid percentiles
try {
p.evaluate(d, 0, d.length, -1.0);
fail();
} catch (IllegalArgumentException ex) {
// success
}
try {
p.evaluate(d, 0, d.length, 101.0);
fail();
} catch (IllegalArgumentException ex) {
// success
}
}
public void testNISTExample() {

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

@ -17,6 +17,8 @@ package org.apache.commons.math.util;
import java.math.BigDecimal;
import org.apache.commons.math.TestUtils;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
@ -556,6 +558,12 @@ public final class MathUtilsTest extends TestCase {
} catch (IllegalArgumentException ex) {
// success
}
// special values
TestUtils.assertEquals(Float.NaN, MathUtils.round(Float.NaN, 2), 0.0f);
assertEquals(0.0f, MathUtils.round(0.0f, 2), 0.0f);
assertEquals(Float.POSITIVE_INFINITY, MathUtils.round(Float.POSITIVE_INFINITY, 2), 0.0f);
assertEquals(Float.NEGATIVE_INFINITY, MathUtils.round(Float.NEGATIVE_INFINITY, 2), 0.0f);
}
public void testRoundDouble() {
@ -646,5 +654,11 @@ public final class MathUtilsTest extends TestCase {
} catch (IllegalArgumentException ex) {
// success
}
// special values
TestUtils.assertEquals(Double.NaN, MathUtils.round(Double.NaN, 2), 0.0);
assertEquals(0.0, MathUtils.round(0.0, 2), 0.0);
assertEquals(Double.POSITIVE_INFINITY, MathUtils.round(Double.POSITIVE_INFINITY, 2), 0.0);
assertEquals(Double.NEGATIVE_INFINITY, MathUtils.round(Double.NEGATIVE_INFINITY, 2), 0.0);
}
}

14
xdocs/changes.xml
View File

@ -50,6 +50,20 @@ Commons Math Release Notes</title>
and numerical utilities, and a PRNG pluggability framework making it
possible to replace the JDK-supplied random number generator in
commons-math (and elsewhere) with alternative PRNG implementations.">
<action dev="brentworden" type="fix" issue="36300" due-to="Nikhil Gupte">
Fixed division by zero error in rounding methods.
</action>
<action dev="brentworden" type="fix" issue="36215" due-to="Mike Hu">
Added upper tail cumulative probability method to HypergeometricDistributionImpl.
</action>
<action dev="brentworden" type="fix" issue="36205" due-to="Xiaogang Zhang">
Added better handling of numerical overflow and division by zero in
Complex calculations.
</action>
<action dev="brentworden" type="fix" issue="36105" due-to="Mikael Weigelt">
Changed ContinuedFraction to better handle infinite convergents that
resulted in divergent continued fraction evaluations.
</action>
<action dev="brentworden" type="fix" issue="35904" due-to="Srinivas Vemury">
Changed rounding methods to not rely on BigDecimal conversions which
was causing numerical error.