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Posted to commits@commons.apache.org by ps...@apache.org on 2009/09/05 19:37:05 UTC
svn commit: r811685 [21/24] - in /commons/proper/math/trunk: ./
src/main/java/org/apache/commons/math/
src/main/java/org/apache/commons/math/analysis/
src/main/java/org/apache/commons/math/analysis/integration/
src/main/java/org/apache/commons/math/ana...
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/MinpackTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/MinpackTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/MinpackTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/MinpackTest.java Sat Sep 5 17:36:48 2009
@@ -33,7 +33,7 @@
/**
* <p>Some of the unit tests are re-implementations of the MINPACK <a
* href="http://www.netlib.org/minpack/ex/file17">file17</a> and <a
- * href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
+ * href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
* The redistribution policy for MINPACK is available <a
* href="http://www.netlib.org/minpack/disclaimer">here</a>, for
* convenience, it is reproduced below.</p>
@@ -134,7 +134,7 @@
minpackTest(new HelicalValleyFunction(new double[] { -100.0, 0.0, 0.0},
991.261822123701), false);
}
-
+
public void testMinpackPowellSingular() {
minpackTest(new PowellSingularFunction(new double[] { 3.0, -1.0, 0.0, 1.0 },
14.6628782986152), false);
@@ -143,7 +143,7 @@
minpackTest(new PowellSingularFunction(new double[] { 300.0, -100.0, 0.0, 100.0 },
126887.903284750), false);
}
-
+
public void testMinpackFreudensteinRoth() {
minpackTest(new FreudensteinRothFunction(new double[] { 0.5, -2.0 },
20.0124960961895, 6.99887517584575,
@@ -164,7 +164,7 @@
-0.89680510749204
}), false);
}
-
+
public void testMinpackBard() {
minpackTest(new BardFunction(1.0, 6.45613629515967, 0.0906359603390466,
new double[] {
@@ -185,7 +185,7 @@
-164464906.857771
}), false);
}
-
+
public void testMinpackKowalikOsborne() {
minpackTest(new KowalikOsborneFunction(new double[] { 0.25, 0.39, 0.415, 0.39 },
0.0728915102882945,
@@ -215,7 +215,7 @@
0.134575665392506
}), false);
}
-
+
public void testMinpackMeyer() {
minpackTest(new MeyerFunction(new double[] { 0.02, 4000.0, 250.0 },
41153.4665543031, 9.37794514651874,
@@ -232,9 +232,9 @@
901.268527953801
}), true);
}
-
+
public void testMinpackWatson() {
-
+
minpackTest(new WatsonFunction(6, 0.0,
5.47722557505166, 0.0478295939097601,
new double[] {
@@ -317,12 +317,12 @@
}), false);
}
-
+
public void testMinpackBox3Dimensional() {
minpackTest(new Box3DimensionalFunction(10, new double[] { 0.0, 10.0, 20.0 },
32.1115837449572), false);
}
-
+
public void testMinpackJennrichSampson() {
minpackTest(new JennrichSampsonFunction(10, new double[] { 0.3, 0.4 },
64.5856498144943, 11.1517793413499,
@@ -354,7 +354,7 @@
-0.403688070279258, 0.236665033746463
}), false);
}
-
+
public void testMinpackChebyquad() {
minpackTest(new ChebyquadFunction(1, 8, 1.0,
1.88623796907732, 1.88623796907732,
@@ -392,7 +392,7 @@
0.833291216194063, 0.940379732824644
}), false);
}
-
+
public void testMinpackBrownAlmostLinear() {
minpackTest(new BrownAlmostLinearFunction(10, 0.5,
16.5302162063499, 0.0,
@@ -411,7 +411,7 @@
0.979430303349865, 0.979430303349865,
0.979430303349865, 0.979430303349865,
0.979430303349865, 1.20569696650135
- }), false);
+ }), false);
minpackTest(new BrownAlmostLinearFunction(10, 50.0,
0.9765625e17, 0.0,
new double[] {
@@ -460,7 +460,7 @@
0.999999999999121
}), false);
}
-
+
public void testMinpackOsborne1() {
minpackTest(new Osborne1Function(new double[] { 0.5, 1.5, -1.0, 0.01, 0.02, },
0.937564021037838, 0.00739249260904843,
@@ -470,9 +470,9 @@
0.0221227011813076
}), false);
}
-
+
public void testMinpackOsborne2() {
-
+
minpackTest(new Osborne2Function(new double[] {
1.3, 0.65, 0.65, 0.7, 0.6,
3.0, 5.0, 7.0, 2.0, 4.5, 5.5
@@ -512,7 +512,7 @@
private static abstract class MinpackFunction
implements DifferentiableMultivariateVectorialFunction, Serializable {
-
+
private static final long serialVersionUID = -6209760235478794233L;
protected int n;
protected int m;
@@ -1025,7 +1025,7 @@
34780.0, 28610.0, 23650.0, 19630.0,
16370.0, 13720.0, 11540.0, 9744.0,
8261.0, 7030.0, 6005.0, 5147.0,
- 4427.0, 3820.0, 3307.0, 2872.0
+ 4427.0, 3820.0, 3307.0, 2872.0
};
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java Sat Sep 5 17:36:48 2009
@@ -40,7 +40,7 @@
/**
* <p>Some of the unit tests are re-implementations of the MINPACK <a
* href="http://www.netlib.org/minpack/ex/file17">file17</a> and <a
- * href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
+ * href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
* The redistribution policy for MINPACK is available <a
* href="http://www.netlib.org/minpack/disclaimer">here</a>, for
* convenience, it is reproduced below.</p>
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexSolverTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexSolverTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexSolverTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexSolverTest.java Sat Sep 5 17:36:48 2009
@@ -41,7 +41,7 @@
SimplexSolver solver = new SimplexSolver();
RealPointValuePair solution = solver.optimize(f, constraints, GoalType.MINIMIZE, true);
-
+
assertEquals(0.0, solution.getPoint()[0], .0000001);
assertEquals(1.0, solution.getPoint()[1], .0000001);
assertEquals(1.0, solution.getPoint()[2], .0000001);
@@ -121,7 +121,7 @@
assertEquals(10.0, solution.getPoint()[0], 0.0);
assertEquals(30.0, solution.getValue(), 0.0);
}
-
+
/**
* With no artificial variables needed (no equals and no greater than
* constraints) we can go straight to Phase 2.
@@ -227,7 +227,7 @@
assertEquals(0.0, solution.getPoint()[2], 0.0);
assertEquals(15.0, solution.getValue(), 0.0);
}
-
+
@Test
public void testTrivialModel() throws OptimizationException {
LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] { 1, 1 }, 0);
@@ -365,7 +365,7 @@
RealPointValuePair solution = solver.optimize(f, constraints, GoalType.MINIMIZE, true);
assertEquals(7518.0, solution.getValue(), .0000001);
}
-
+
/**
* Converts a test string to a {@link LinearConstraint}.
* Ex: x0 + x1 + x2 + x3 - x12 = 0
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexTableauTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexTableauTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexTableauTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/linear/SimplexTableauTest.java Sat Sep 5 17:36:48 2009
@@ -27,7 +27,7 @@
public class SimplexTableauTest extends TestCase {
- public void testInitialization() {
+ public void testInitialization() {
LinearObjectiveFunction f = createFunction();
Collection<LinearConstraint> constraints = createConstraints();
SimplexTableau tableau =
@@ -42,7 +42,7 @@
assertMatrixEquals(expectedInitialTableau, tableau.getData());
}
- public void testdiscardArtificialVariables() {
+ public void testdiscardArtificialVariables() {
LinearObjectiveFunction f = createFunction();
Collection<LinearConstraint> constraints = createConstraints();
SimplexTableau tableau =
@@ -62,7 +62,7 @@
Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
constraints.add(new LinearConstraint(new double[] {1, 0}, Relationship.LEQ, 2));
constraints.add(new LinearConstraint(new double[] {0, 1}, Relationship.LEQ, 3));
- constraints.add(new LinearConstraint(new double[] {1, 1}, Relationship.LEQ, 4));
+ constraints.add(new LinearConstraint(new double[] {1, 1}, Relationship.LEQ, 4));
SimplexTableau tableau =
new SimplexTableau(f, constraints, GoalType.MAXIMIZE, false, 1.0e-6);
double[][] initialTableau = {
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/univariate/BrentMinimizerTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/univariate/BrentMinimizerTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/univariate/BrentMinimizerTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/univariate/BrentMinimizerTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -31,7 +31,7 @@
import org.junit.Test;
/**
- * @version $Revision$ $Date$
+ * @version $Revision$ $Date$
*/
public final class BrentMinimizerTest {
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/AbstractRandomGeneratorTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/AbstractRandomGeneratorTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/AbstractRandomGeneratorTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/AbstractRandomGeneratorTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -19,7 +19,7 @@
import junit.framework.TestSuite;
import org.apache.commons.math.stat.Frequency;
-
+
/**
* Test cases for the AbstractRandomGenerator class
@@ -28,20 +28,20 @@
*/
public class AbstractRandomGeneratorTest extends RandomDataTest {
-
+
protected TestRandomGenerator testGenerator = new TestRandomGenerator();
-
+
public AbstractRandomGeneratorTest(String name) {
super(name);
randomData = new RandomDataImpl(testGenerator);
- }
-
+ }
+
public static Test suite() {
TestSuite suite = new TestSuite(AbstractRandomGeneratorTest.class);
suite.setName("AbstractRandomGenerator Tests");
return suite;
}
-
+
@Override
public void testNextInt() {
try {
@@ -55,26 +55,26 @@
for (int i=0; i<smallSampleSize; i++) {
value = testGenerator.nextInt(4);
assertTrue("nextInt range",(value >= 0) && (value <= 3));
- freq.addValue(value);
+ freq.addValue(value);
}
long[] observed = new long[4];
for (int i=0; i<4; i++) {
observed[i] = freq.getCount(i);
- }
-
+ }
+
/* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
* Change to 11.34 for alpha = .01
*/
assertTrue("chi-square test -- will fail about 1 in 1000 times",
- testStatistic.chiSquare(expected,observed) < 16.27);
+ testStatistic.chiSquare(expected,observed) < 16.27);
}
-
+
@Override
public void testNextLong() {
long q1 = Long.MAX_VALUE/4;
long q2 = 2 * q1;
long q3 = 3 * q1;
-
+
Frequency freq = new Frequency();
long val = 0;
int value = 0;
@@ -89,22 +89,22 @@
} else {
value = 3;
}
- freq.addValue(value);
+ freq.addValue(value);
}
long[] observed = new long[4];
for (int i=0; i<4; i++) {
observed[i] = freq.getCount(i);
- }
-
+ }
+
/* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
* Change to 11.34 for alpha = .01
*/
assertTrue("chi-square test -- will fail about 1 in 1000 times",
- testStatistic.chiSquare(expected,observed) < 16.27);
+ testStatistic.chiSquare(expected,observed) < 16.27);
}
-
+
public void testNextBoolean() {
- long halfSampleSize = smallSampleSize / 2;
+ long halfSampleSize = smallSampleSize / 2;
double[] expected = {halfSampleSize, halfSampleSize};
long[] observed = new long[2];
for (int i=0; i<smallSampleSize; i++) {
@@ -118,9 +118,9 @@
* Change to 6.635 for alpha = .01
*/
assertTrue("chi-square test -- will fail about 1 in 1000 times",
- testStatistic.chiSquare(expected,observed) < 10.828);
+ testStatistic.chiSquare(expected,observed) < 10.828);
}
-
+
public void testNextFloat() {
Frequency freq = new Frequency();
float val = 0;
@@ -136,17 +136,17 @@
} else {
value = 3;
}
- freq.addValue(value);
+ freq.addValue(value);
}
long[] observed = new long[4];
for (int i=0; i<4; i++) {
observed[i] = freq.getCount(i);
- }
-
+ }
+
/* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
* Change to 11.34 for alpha = .01
*/
assertTrue("chi-square test -- will fail about 1 in 1000 times",
- testStatistic.chiSquare(expected,observed) < 16.27);
+ testStatistic.chiSquare(expected,observed) < 16.27);
}
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/EmpiricalDistributionTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/EmpiricalDistributionTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/EmpiricalDistributionTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/EmpiricalDistributionTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -42,9 +42,9 @@
protected EmpiricalDistribution empiricalDistribution = null;
protected EmpiricalDistribution empiricalDistribution2 = null;
protected File file = null;
- protected URL url = null;
+ protected URL url = null;
protected double[] dataArray = null;
-
+
public EmpiricalDistributionTest(String name) {
super(name);
}
@@ -53,9 +53,9 @@
public void setUp() throws IOException {
empiricalDistribution = new EmpiricalDistributionImpl(100);
url = getClass().getResource("testData.txt");
-
+
empiricalDistribution2 = new EmpiricalDistributionImpl(100);
- BufferedReader in =
+ BufferedReader in =
new BufferedReader(new InputStreamReader(
url.openStream()));
String str = null;
@@ -65,13 +65,13 @@
}
in.close();
in = null;
-
+
dataArray = new double[list.size()];
int i = 0;
for (Double data : list) {
dataArray[i] = data.doubleValue();
i++;
- }
+ }
}
public static Test suite() {
@@ -81,12 +81,12 @@
}
/**
- * Test EmpiricalDistrbution.load() using sample data file.<br>
- * Check that the sampleCount, mu and sigma match data in
+ * Test EmpiricalDistrbution.load() using sample data file.<br>
+ * Check that the sampleCount, mu and sigma match data in
* the sample data file.
*/
public void testLoad() throws Exception {
- empiricalDistribution.load(url);
+ empiricalDistribution.load(url);
// testData File has 10000 values, with mean ~ 5.0, std dev ~ 1
// Make sure that loaded distribution matches this
assertEquals(empiricalDistribution.getSampleStats().getN(),1000,10E-7);
@@ -101,12 +101,12 @@
/**
* Test EmpiricalDistrbution.load(double[]) using data taken from
- * sample data file.<br>
- * Check that the sampleCount, mu and sigma match data in
+ * sample data file.<br>
+ * Check that the sampleCount, mu and sigma match data in
* the sample data file.
*/
public void testDoubleLoad() throws Exception {
- empiricalDistribution2.load(dataArray);
+ empiricalDistribution2.load(dataArray);
// testData File has 10000 values, with mean ~ 5.0, std dev ~ 1
// Make sure that loaded distribution matches this
assertEquals(empiricalDistribution2.getSampleStats().getN(),1000,10E-7);
@@ -117,14 +117,14 @@
assertEquals
(empiricalDistribution2.getSampleStats().getStandardDeviation(),
1.0173699343977738,10E-7);
-
+
double[] bounds = empiricalDistribution2.getUpperBounds();
assertEquals(bounds.length, 100);
assertEquals(bounds[99], 1.0, 10e-12);
-
+
}
-
- /**
+
+ /**
* Generate 1000 random values and make sure they look OK.<br>
* Note that there is a non-zero (but very small) probability that
* these tests will fail even if the code is working as designed.
@@ -133,7 +133,7 @@
tstGen(0.1);
tstDoubleGen(0.1);
}
-
+
/**
* Make sure exception thrown if digest getNext is attempted
* before loading empiricalDistribution.
@@ -149,17 +149,17 @@
fail("wrong exception caught");
}
}
-
+
/**
* Make sure we can handle a grid size that is too fine
*/
public void testGridTooFine() throws Exception {
empiricalDistribution = new EmpiricalDistributionImpl(1001);
- tstGen(0.1);
- empiricalDistribution2 = new EmpiricalDistributionImpl(1001);
+ tstGen(0.1);
+ empiricalDistribution2 = new EmpiricalDistributionImpl(1001);
tstDoubleGen(0.1);
}
-
+
/**
* How about too fat?
*/
@@ -167,10 +167,10 @@
empiricalDistribution = new EmpiricalDistributionImpl(1);
tstGen(5); // ridiculous tolerance; but ridiculous grid size
// really just checking to make sure we do not bomb
- empiricalDistribution2 = new EmpiricalDistributionImpl(1);
- tstDoubleGen(5);
+ empiricalDistribution2 = new EmpiricalDistributionImpl(1);
+ tstDoubleGen(5);
}
-
+
/**
* Test bin index overflow problem (BZ 36450)
*/
@@ -178,15 +178,15 @@
double[] x = new double[] {9474.94326071674, 2080107.8865462579};
new EmpiricalDistributionImpl().load(x);
}
-
+
public void testSerialization() {
// Empty
EmpiricalDistribution dist = new EmpiricalDistributionImpl();
EmpiricalDistribution dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(dist);
verifySame(dist, dist2);
-
+
// Loaded
- empiricalDistribution2.load(dataArray);
+ empiricalDistribution2.load(dataArray);
dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(empiricalDistribution2);
verifySame(empiricalDistribution2, dist2);
}
@@ -238,9 +238,9 @@
assertEquals(d1.getBinStats(), d2.getBinStats());
}
}
-
+
private void tstGen(double tolerance)throws Exception {
- empiricalDistribution.load(url);
+ empiricalDistribution.load(url);
SummaryStatistics stats = new SummaryStatistics();
for (int i = 1; i < 1000; i++) {
stats.addValue(empiricalDistribution.getNextValue());
@@ -251,7 +251,7 @@
}
private void tstDoubleGen(double tolerance)throws Exception {
- empiricalDistribution2.load(dataArray);
+ empiricalDistribution2.load(dataArray);
SummaryStatistics stats = new SummaryStatistics();
for (int i = 1; i < 1000; i++) {
stats.addValue(empiricalDistribution2.getNextValue());
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/MersenneTwisterTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/MersenneTwisterTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/MersenneTwisterTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/MersenneTwisterTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -276,7 +276,7 @@
950049240l, 4173257693l, 1760124957l, 512151405l, 681175196l, 580563018l, 1169662867l, 4015033554l,
2687781101l, 699691603l, 2673494188l, 1137221356l, 123599888l, 472658308l, 1053598179l, 1012713758l,
3481064843l, 3759461013l, 3981457956l, 3830587662l, 1877191791l, 3650996736l, 988064871l, 3515461600l,
- 4089077232l, 2225147448l, 1249609188l, 2643151863l, 3896204135l, 2416995901l, 1397735321l, 3460025646l
+ 4089077232l, 2225147448l, 1249609188l, 2643151863l, 3896204135l, 2416995901l, 1397735321l, 3460025646l
};
double[] refDouble = {
0.76275443, 0.99000644, 0.98670464, 0.10143112, 0.27933125, 0.69867227, 0.94218740, 0.03427201,
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomAdaptorTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomAdaptorTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomAdaptorTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomAdaptorTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -26,29 +26,29 @@
*/
public class RandomAdaptorTest extends RandomDataTest {
-
+
public RandomAdaptorTest(String name) {
super(name);
- }
-
+ }
+
public static Test suite() {
TestSuite suite = new TestSuite(RandomAdaptorTest.class);
suite.setName("RandomAdaptor Tests");
return suite;
}
-
+
public void testAdaptor() {
ConstantGenerator generator = new ConstantGenerator();
Random random = RandomAdaptor.createAdaptor(generator);
checkConstant(random);
RandomAdaptor randomAdaptor = new RandomAdaptor(generator);
- checkConstant(randomAdaptor);
+ checkConstant(randomAdaptor);
}
-
+
private void checkConstant(Random random) {
byte[] bytes = new byte[] {0};
random.nextBytes(bytes);
- assertEquals(0, bytes[0]);
+ assertEquals(0, bytes[0]);
assertEquals(false, random.nextBoolean());
assertEquals(0, random.nextDouble(), 0);
assertEquals(0, random.nextFloat(), 0);
@@ -59,18 +59,18 @@
random.setSeed(100);
assertEquals(0, random.nextDouble(), 0);
}
-
+
/*
* "Constant" generator to test Adaptor delegation.
* "Powered by Eclipse ;-)"
- *
+ *
*/
private static class ConstantGenerator implements RandomGenerator {
-
+
public boolean nextBoolean() {
return false;
}
-
+
public void nextBytes(byte[] bytes) {
}
@@ -100,7 +100,7 @@
public void setSeed(int seed) {
}
-
+
public void setSeed(int[] seed) {
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -27,7 +27,7 @@
/**
* Test cases for the RandomData class.
- *
+ *
* @version $Revision$ $Date: 2009-04-05 11:55:59 -0500 (Sun, 05 Apr
* 2009) $
*/
@@ -451,7 +451,7 @@
/*
* remove this test back soon, since it takes about 4 seconds
- *
+ *
* try { randomData.setSecureAlgorithm("SHA1PRNG","SUN"); } catch
* (NoSuchProviderException ex) { ; } assertTrue("different seeds",
* !hex.equals(randomData.nextSecureHexString(40))); try {
@@ -459,7 +459,7 @@
* fail("expecting NoSuchAlgorithmException"); } catch
* (NoSuchProviderException ex) { ; } catch (NoSuchAlgorithmException
* ex) { ; }
- *
+ *
* try { randomData.setSecureAlgorithm("SHA1PRNG","NOSUCHPROVIDER");
* fail("expecting NoSuchProviderException"); } catch
* (NoSuchProviderException ex) { ; }
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/TestRandomGenerator.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/TestRandomGenerator.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/TestRandomGenerator.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/TestRandomGenerator.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -18,7 +18,7 @@
import java.util.Random;
/**
- * Dummy AbstractRandomGenerator concrete subclass that just wraps a
+ * Dummy AbstractRandomGenerator concrete subclass that just wraps a
* java.util.Random instance. Used by AbstractRandomGeneratorTest to test
* default implementations in AbstractRandomGenerator.
*
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/UniformRandomGeneratorTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/UniformRandomGeneratorTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/UniformRandomGeneratorTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/UniformRandomGeneratorTest.java Sat Sep 5 17:36:48 2009
@@ -39,8 +39,8 @@
assertEquals(0.0, StatUtils.mean(sample), 0.07);
assertEquals(1.0, StatUtils.variance(sample), 0.02);
}
-
-
+
+
public static Test suite() {
return new TestSuite(UniformRandomGeneratorTest.class);
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/ValueServerTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/ValueServerTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/ValueServerTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/ValueServerTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -24,7 +24,7 @@
import org.apache.commons.math.RetryTestCase;
import org.apache.commons.math.stat.descriptive.SummaryStatistics;
-
+
/**
* Test cases for the ValueServer class.
*
@@ -34,7 +34,7 @@
public final class ValueServerTest extends RetryTestCase {
private ValueServer vs = new ValueServer();
-
+
public ValueServerTest(String name) {
super(name);
}
@@ -44,7 +44,7 @@
vs.setMode(ValueServer.DIGEST_MODE);
try {
URL url = getClass().getResource("testData.txt");
- vs.setValuesFileURL(url);
+ vs.setValuesFileURL(url);
} catch (Exception ex) {
fail("malformed test URL");
}
@@ -56,8 +56,8 @@
return suite;
}
-
- /**
+
+ /**
* Generate 1000 random values and make sure they look OK.<br>
* Note that there is a non-zero (but very small) probability that
* these tests will fail even if the code is working as designed.
@@ -66,31 +66,31 @@
double next = 0.0;
double tolerance = 0.1;
vs.computeDistribution();
- assertTrue("empirical distribution property",
+ assertTrue("empirical distribution property",
vs.getEmpiricalDistribution() != null);
SummaryStatistics stats = new SummaryStatistics();
for (int i = 1; i < 1000; i++) {
next = vs.getNext();
stats.addValue(next);
- }
+ }
assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
assertEquals
- ("std dev", 1.0173699343977738, stats.getStandardDeviation(),
+ ("std dev", 1.0173699343977738, stats.getStandardDeviation(),
tolerance);
-
+
vs.computeDistribution(500);
stats = new SummaryStatistics();
for (int i = 1; i < 1000; i++) {
next = vs.getNext();
stats.addValue(next);
- }
+ }
assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
assertEquals
- ("std dev", 1.0173699343977738, stats.getStandardDeviation(),
+ ("std dev", 1.0173699343977738, stats.getStandardDeviation(),
tolerance);
-
+
}
-
+
/**
* Make sure exception thrown if digest getNext is attempted
* before loading empiricalDistribution.
@@ -131,7 +131,7 @@
}
/**
- * Test ValueServer REPLAY_MODE using values in testData file.<br>
+ * Test ValueServer REPLAY_MODE using values in testData file.<br>
* Check that the values 1,2,1001,1002 match data file values 1 and 2.
* the sample data file.
*/
@@ -157,8 +157,8 @@
// make sure no NPE
vs.closeReplayFile();
}
-
- /**
+
+ /**
* Test other ValueServer modes
*/
public void testModes() throws Exception {
@@ -185,7 +185,7 @@
// ignored
}
}
-
+
/**
* Test fill
*/
@@ -202,7 +202,7 @@
assertEquals("fill test in place",2,v2[i],Double.MIN_VALUE);
}
}
-
+
/**
* Test getters to make Clover happy
*/
@@ -213,5 +213,5 @@
URL url = vs.getValuesFileURL();
assertEquals("valuesFileURL test","http://www.apache.org",url.toString());
}
-
+
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/BetaTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/BetaTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/BetaTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/BetaTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -60,60 +60,60 @@
public void testRegularizedBetaPositivePositiveNan() {
testRegularizedBeta(Double.NaN, 0.5, 1.0, Double.NaN);
}
-
+
public void testRegularizedBetaNegativePositivePositive() {
testRegularizedBeta(Double.NaN, -0.5, 1.0, 2.0);
}
-
+
public void testRegularizedBetaPositiveNegativePositive() {
testRegularizedBeta(Double.NaN, 0.5, -1.0, 2.0);
}
-
+
public void testRegularizedBetaPositivePositiveNegative() {
testRegularizedBeta(Double.NaN, 0.5, 1.0, -2.0);
}
-
+
public void testRegularizedBetaZeroPositivePositive() {
testRegularizedBeta(0.0, 0.0, 1.0, 2.0);
}
-
+
public void testRegularizedBetaPositiveZeroPositive() {
testRegularizedBeta(Double.NaN, 0.5, 0.0, 2.0);
}
-
+
public void testRegularizedBetaPositivePositiveZero() {
testRegularizedBeta(Double.NaN, 0.5, 1.0, 0.0);
}
-
+
public void testRegularizedBetaPositivePositivePositive() {
testRegularizedBeta(0.75, 0.5, 1.0, 2.0);
}
-
+
public void testLogBetaNanPositive() {
testLogBeta(Double.NaN, Double.NaN, 2.0);
}
-
+
public void testLogBetaPositiveNan() {
testLogBeta(Double.NaN, 1.0, Double.NaN);
}
-
+
public void testLogBetaNegativePositive() {
testLogBeta(Double.NaN, -1.0, 2.0);
}
-
+
public void testLogBetaPositiveNegative() {
testLogBeta(Double.NaN, 1.0, -2.0);
}
-
+
public void testLogBetaZeroPositive() {
testLogBeta(Double.NaN, 0.0, 2.0);
}
-
+
public void testLogBetaPositiveZero() {
testLogBeta(Double.NaN, 1.0, 0.0);
}
-
+
public void testLogBetaPositivePositive() {
testLogBeta(-0.693147180559945, 1.0, 2.0);
}
-}
\ No newline at end of file
+}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/ErfTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/ErfTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/ErfTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/ErfTest.java Sat Sep 5 17:36:48 2009
@@ -48,7 +48,7 @@
double actual = Erf.erf(x);
double expected = 0.99;
assertEquals(expected, actual, 1.0e-5);
-
+
actual = Erf.erf(-x);
expected = -expected;
assertEquals(expected, actual, 1.0e-5);
@@ -59,7 +59,7 @@
double actual = Erf.erf(x);
double expected = 0.995;
assertEquals(expected, actual, 1.0e-5);
-
+
actual = Erf.erf(-x);
expected = -expected;
assertEquals(expected, actual, 1.0e-5);
@@ -70,7 +70,7 @@
double actual = Erf.erf(x);
double expected = 0.999;
assertEquals(expected, actual, 1.0e-5);
-
+
actual = Erf.erf(-x);
expected = -expected;
assertEquals(expected, actual, 1.0e-5);
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/GammaTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/GammaTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/GammaTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/special/GammaTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -25,7 +25,7 @@
* @version $Revision$ $Date$
*/
public class GammaTest extends TestCase {
-
+
public GammaTest(String name) {
super(name);
}
@@ -53,39 +53,39 @@
public void testRegularizedGammaPositiveNan() {
testRegularizedGamma(Double.NaN, 1.0, Double.NaN);
}
-
+
public void testRegularizedGammaNegativePositive() {
testRegularizedGamma(Double.NaN, -1.5, 1.0);
}
-
+
public void testRegularizedGammaPositiveNegative() {
testRegularizedGamma(Double.NaN, 1.0, -1.0);
}
-
+
public void testRegularizedGammaZeroPositive() {
testRegularizedGamma(Double.NaN, 0.0, 1.0);
}
-
+
public void testRegularizedGammaPositiveZero() {
testRegularizedGamma(0.0, 1.0, 0.0);
}
-
+
public void testRegularizedGammaPositivePositive() {
testRegularizedGamma(0.632120558828558, 1.0, 1.0);
}
-
+
public void testLogGammaNan() {
testLogGamma(Double.NaN, Double.NaN);
}
-
+
public void testLogGammaNegative() {
testLogGamma(Double.NaN, -1.0);
}
-
+
public void testLogGammaZero() {
testLogGamma(Double.NaN, 0.0);
}
-
+
public void testLogGammaPositive() {
testLogGamma(0.6931471805599457, 3.0);
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/CertifiedDataTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/CertifiedDataTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/CertifiedDataTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/CertifiedDataTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -61,20 +61,20 @@
SummaryStatistics u = new SummaryStatistics();
loadStats("data/PiDigits.txt", u);
assertEquals("PiDigits: std", std, u.getStandardDeviation(), 1E-13);
- assertEquals("PiDigits: mean", mean, u.getMean(), 1E-13);
+ assertEquals("PiDigits: mean", mean, u.getMean(), 1E-13);
loadStats("data/Mavro.txt", u);
assertEquals("Mavro: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("Mavro: mean", mean, u.getMean(), 1E-14);
-
+
loadStats("data/Michelso.txt", u);
assertEquals("Michelso: std", std, u.getStandardDeviation(), 1E-13);
- assertEquals("Michelso: mean", mean, u.getMean(), 1E-13);
-
+ assertEquals("Michelso: mean", mean, u.getMean(), 1E-13);
+
loadStats("data/NumAcc1.txt", u);
assertEquals("NumAcc1: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("NumAcc1: mean", mean, u.getMean(), 1E-14);
-
+
loadStats("data/NumAcc2.txt", u);
assertEquals("NumAcc2: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("NumAcc2: mean", mean, u.getMean(), 1E-14);
@@ -87,23 +87,23 @@
public void testDescriptiveStatistics() throws Exception {
DescriptiveStatistics u = new DescriptiveStatistics();
-
+
loadStats("data/PiDigits.txt", u);
assertEquals("PiDigits: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("PiDigits: mean", mean, u.getMean(), 1E-14);
-
+
loadStats("data/Mavro.txt", u);
assertEquals("Mavro: std", std, u.getStandardDeviation(), 1E-14);
- assertEquals("Mavro: mean", mean, u.getMean(), 1E-14);
-
+ assertEquals("Mavro: mean", mean, u.getMean(), 1E-14);
+
loadStats("data/Michelso.txt", u);
assertEquals("Michelso: std", std, u.getStandardDeviation(), 1E-14);
- assertEquals("Michelso: mean", mean, u.getMean(), 1E-14);
+ assertEquals("Michelso: mean", mean, u.getMean(), 1E-14);
loadStats("data/NumAcc1.txt", u);
assertEquals("NumAcc1: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("NumAcc1: mean", mean, u.getMean(), 1E-14);
-
+
loadStats("data/NumAcc2.txt", u);
assertEquals("NumAcc2: std", std, u.getStandardDeviation(), 1E-14);
assertEquals("NumAcc2: mean", mean, u.getMean(), 1E-14);
@@ -115,7 +115,7 @@
* @param statistical summary
*/
private void loadStats(String resource, Object u) throws Exception {
-
+
DescriptiveStatistics d = null;
SummaryStatistics s = null;
if (u instanceof DescriptiveStatistics) {
@@ -127,14 +127,14 @@
"clear", new Class[]{}).invoke(u, new Object[]{});
mean = Double.NaN;
std = Double.NaN;
-
+
BufferedReader in =
new BufferedReader(
new InputStreamReader(
CertifiedDataTest.class.getResourceAsStream(resource)));
-
+
String line = null;
-
+
for (int j = 0; j < 60; j++) {
line = in.readLine();
if (j == 40) {
@@ -148,9 +148,9 @@
line.substring(line.lastIndexOf(":") + 1).trim());
}
}
-
+
line = in.readLine();
-
+
while (line != null) {
if (d != null) {
d.addValue(Double.parseDouble(line.trim()));
@@ -159,7 +159,7 @@
}
line = in.readLine();
}
-
+
in.close();
}
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/FrequencyTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/FrequencyTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/FrequencyTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/FrequencyTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -42,22 +42,22 @@
private int threeI=3;
private double tolerance = 10E-15;
private Frequency f = null;
-
+
public FrequencyTest(String name) {
super(name);
}
@Override
- public void setUp() {
+ public void setUp() {
f = new Frequency();
}
-
+
public static Test suite() {
TestSuite suite = new TestSuite(FrequencyTest.class);
suite.setName("Frequency Tests");
return suite;
}
-
+
/** test freq counts */
public void testCounts() {
assertEquals("total count",0,f.getSumFreq());
@@ -75,10 +75,10 @@
assertEquals("Integer argument cum freq",4, f.getCumFreq(Integer.valueOf(2)));
assertEquals("five cumulative frequency", 4, f.getCumFreq(5));
assertEquals("foo cumulative frequency", 0, f.getCumFreq("foo"));
-
+
f.clear();
assertEquals("total count",0,f.getSumFreq());
-
+
// userguide examples -------------------------------------------------------------------
f.addValue("one");
f.addValue("One");
@@ -89,7 +89,7 @@
assertEquals("z cumulative pct", 1.0, f.getCumPct("z"), tolerance);
assertEquals("Ot cumulative pct", 0.25, f.getCumPct("Ot"), tolerance);
f.clear();
-
+
f = null;
Frequency f = new Frequency();
f.addValue(1);
@@ -102,8 +102,8 @@
assertEquals("0 cum pct", 0.2, f.getCumPct(0), tolerance);
assertEquals("1 pct", 0.6, f.getPct(Integer.valueOf(1)), tolerance);
assertEquals("-2 cum pct", 0, f.getCumPct(-2), tolerance);
- assertEquals("10 cum pct", 1, f.getCumPct(10), tolerance);
-
+ assertEquals("10 cum pct", 1, f.getCumPct(10), tolerance);
+
f = null;
f = new Frequency(String.CASE_INSENSITIVE_ORDER);
f.addValue("one");
@@ -129,8 +129,8 @@
assertEquals(0.25, f.getPct('a'), 0.0);
assertEquals(0.5, f.getCumPct('b'), 0.0);
assertEquals(1.0, f.getCumPct('e'), 0.0);
- }
-
+ }
+
/** test pcts */
public void testPcts() {
f.addValue(oneL);
@@ -154,7 +154,7 @@
assertEquals("zero cum pct",0.0,f.getCumPct(0),tolerance);
assertEquals("foo cum pct",0,f.getCumPct("foo"),tolerance);
}
-
+
/** test adding incomparable values */
public void testAdd() {
char aChar = 'a';
@@ -163,7 +163,7 @@
f.addValue(aChar);
f.addValue(bChar);
try {
- f.addValue(aString);
+ f.addValue(aString);
fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// expected
@@ -178,17 +178,17 @@
assertEquals("b cum pct",1.0,f.getCumPct(bChar),tolerance);
assertEquals("a string pct",0.0,f.getPct(aString),tolerance);
assertEquals("a string cum pct",0.0,f.getCumPct(aString),tolerance);
-
+
f = new Frequency();
f.addValue("One");
try {
- f.addValue(new Integer("One"));
+ f.addValue(new Integer("One"));
fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// expected
}
}
-
+
// Check what happens when non-Comparable objects are added
@SuppressWarnings("deprecation")
public void testAddNonComparable(){
@@ -216,18 +216,18 @@
assertTrue("pct, empty table", Double.isNaN(f.getPct(0)));
assertTrue("pct, empty table", Double.isNaN(f.getPct(Integer.valueOf(0))));
assertTrue("cum pct, empty table", Double.isNaN(f.getCumPct(0)));
- assertTrue("cum pct, empty table", Double.isNaN(f.getCumPct(Integer.valueOf(0))));
+ assertTrue("cum pct, empty table", Double.isNaN(f.getCumPct(Integer.valueOf(0))));
}
-
+
/**
- * Tests toString()
+ * Tests toString()
*/
public void testToString(){
f.addValue(oneL);
f.addValue(twoL);
f.addValue(oneI);
f.addValue(twoI);
-
+
String s = f.toString();
//System.out.println(s);
assertNotNull(s);
@@ -235,10 +235,10 @@
try {
String line = reader.readLine(); // header line
assertNotNull(line);
-
+
line = reader.readLine(); // one's or two's line
assertNotNull(line);
-
+
line = reader.readLine(); // one's or two's line
assertNotNull(line);
@@ -246,7 +246,7 @@
assertNull(line);
} catch(IOException ex){
fail(ex.getMessage());
- }
+ }
}
public void testIntegerValues() {
Comparable<?> obj1 = null;
@@ -265,9 +265,9 @@
Iterator<?> it = f.valuesIterator();
while (it.hasNext()) {
assertTrue(it.next() instanceof Long);
- }
+ }
}
-
+
public void testSerial() {
f.addValue(oneL);
f.addValue(twoL);
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/StatUtilsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/StatUtilsTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/StatUtilsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/StatUtilsTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -117,10 +117,10 @@
}
}
-
+
public void testSumSq() {
double[] x = null;
-
+
// test null
try {
StatUtils.sumSq(x);
@@ -128,33 +128,33 @@
} catch (IllegalArgumentException ex) {
// success
}
-
+
try {
StatUtils.sumSq(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.sumSq(x), tolerance);
TestUtils.assertEquals(Double.NaN, StatUtils.sumSq(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(4, StatUtils.sumSq(x), tolerance);
TestUtils.assertEquals(4, StatUtils.sumSq(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(18, StatUtils.sumSq(x), tolerance);
TestUtils.assertEquals(8, StatUtils.sumSq(x, 1, 2), tolerance);
}
-
+
public void testProduct() {
double[] x = null;
-
+
// test null
try {
StatUtils.product(x);
@@ -162,33 +162,33 @@
} catch (IllegalArgumentException ex) {
// success
}
-
+
try {
StatUtils.product(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.product(x), tolerance);
TestUtils.assertEquals(Double.NaN, StatUtils.product(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(two, StatUtils.product(x), tolerance);
TestUtils.assertEquals(two, StatUtils.product(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(12, StatUtils.product(x), tolerance);
TestUtils.assertEquals(4, StatUtils.product(x, 1, 2), tolerance);
}
-
+
public void testSumLog() {
double[] x = null;
-
+
// test null
try {
StatUtils.sumLog(x);
@@ -196,98 +196,98 @@
} catch (IllegalArgumentException ex) {
// success
}
-
+
try {
StatUtils.sumLog(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.sumLog(x), tolerance);
TestUtils.assertEquals(Double.NaN, StatUtils.sumLog(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(Math.log(two), StatUtils.sumLog(x), tolerance);
TestUtils.assertEquals(Math.log(two), StatUtils.sumLog(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(Math.log(one) + 2.0 * Math.log(two) + Math.log(three), StatUtils.sumLog(x), tolerance);
TestUtils.assertEquals(2.0 * Math.log(two), StatUtils.sumLog(x, 1, 2), tolerance);
}
-
+
public void testMean() {
double[] x = null;
-
+
try {
StatUtils.mean(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.mean(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(two, StatUtils.mean(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(2.5, StatUtils.mean(x, 2, 2), tolerance);
}
-
+
public void testVariance() {
double[] x = null;
-
+
try {
StatUtils.variance(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.variance(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(0.0, StatUtils.variance(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(0.5, StatUtils.variance(x, 2, 2), tolerance);
-
+
// test precomputed mean
x = new double[] {one, two, two, three};
TestUtils.assertEquals(0.5, StatUtils.variance(x,2.5, 2, 2), tolerance);
}
-
+
public void testMax() {
double[] x = null;
-
+
try {
StatUtils.max(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.max(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(two, StatUtils.max(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(three, StatUtils.max(x, 1, 3), tolerance);
@@ -299,7 +299,7 @@
// test middle nan is ignored
x = new double[] {one, nan, three};
TestUtils.assertEquals(three, StatUtils.max(x), tolerance);
-
+
// test last nan is ignored
x = new double[] {one, two, nan};
TestUtils.assertEquals(two, StatUtils.max(x), tolerance);
@@ -308,25 +308,25 @@
x = new double[] {nan, nan, nan};
TestUtils.assertEquals(nan, StatUtils.max(x), tolerance);
}
-
+
public void testMin() {
double[] x = null;
-
+
try {
StatUtils.min(x, 0, 4);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.min(x, 0, 0), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(two, StatUtils.min(x, 0, 1), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(two, StatUtils.min(x, 1, 3), tolerance);
@@ -338,7 +338,7 @@
// test middle nan is ignored
x = new double[] {one, nan, three};
TestUtils.assertEquals(one, StatUtils.min(x), tolerance);
-
+
// test last nan is ignored
x = new double[] {one, two, nan};
TestUtils.assertEquals(one, StatUtils.min(x), tolerance);
@@ -347,10 +347,10 @@
x = new double[] {nan, nan, nan};
TestUtils.assertEquals(nan, StatUtils.min(x), tolerance);
}
-
+
public void testPercentile() {
double[] x = null;
-
+
// test null
try {
StatUtils.percentile(x, .25);
@@ -358,30 +358,30 @@
} catch (IllegalArgumentException ex) {
// success
}
-
+
try {
StatUtils.percentile(x, 0, 4, 0.25);
fail("null is not a valid data array.");
} catch (IllegalArgumentException ex) {
// success
}
-
+
// test empty
x = new double[] {};
TestUtils.assertEquals(Double.NaN, StatUtils.percentile(x, 25), tolerance);
TestUtils.assertEquals(Double.NaN, StatUtils.percentile(x, 0, 0, 25), tolerance);
-
+
// test one
x = new double[] {two};
TestUtils.assertEquals(two, StatUtils.percentile(x, 25), tolerance);
TestUtils.assertEquals(two, StatUtils.percentile(x, 0, 1, 25), tolerance);
-
+
// test many
x = new double[] {one, two, two, three};
TestUtils.assertEquals(2.5, StatUtils.percentile(x, 70), tolerance);
TestUtils.assertEquals(2.5, StatUtils.percentile(x, 1, 3, 62.5), tolerance);
}
-
+
public void testDifferenceStats() throws Exception {
double sample1[] = {1d, 2d, 3d, 4d};
double sample2[] = {1d, 3d, 4d, 2d};
@@ -390,7 +390,7 @@
double meanDifference = StatUtils.meanDifference(sample1, sample2);
assertEquals(StatUtils.sumDifference(sample1, sample2), StatUtils.sum(diff), tolerance);
assertEquals(meanDifference, StatUtils.mean(diff), tolerance);
- assertEquals(StatUtils.varianceDifference(sample1, sample2, meanDifference),
+ assertEquals(StatUtils.varianceDifference(sample1, sample2, meanDifference),
StatUtils.variance(diff), tolerance);
try {
StatUtils.meanDifference(sample1, small);
@@ -412,7 +412,7 @@
// expected
}
}
-
+
public void testGeometricMean() throws Exception {
double[] test = null;
try {
@@ -422,9 +422,9 @@
// expected
}
test = new double[] {2, 4, 6, 8};
- assertEquals(Math.exp(0.25d * StatUtils.sumLog(test)),
+ assertEquals(Math.exp(0.25d * StatUtils.sumLog(test)),
StatUtils.geometricMean(test), Double.MIN_VALUE);
- assertEquals(Math.exp(0.5 * StatUtils.sumLog(test, 0, 2)),
+ assertEquals(Math.exp(0.5 * StatUtils.sumLog(test, 0, 2)),
StatUtils.geometricMean(test, 0, 2), Double.MIN_VALUE);
}
-}
\ No newline at end of file
+}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/clustering/EuclideanIntegerPointTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/clustering/EuclideanIntegerPointTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/clustering/EuclideanIntegerPointTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/clustering/EuclideanIntegerPointTest.java Sat Sep 5 17:36:48 2009
@@ -5,9 +5,9 @@
* 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.
@@ -33,7 +33,7 @@
int[] array = { -3, -2, -1, 0, 1 };
assertTrue(array == new EuclideanIntegerPoint(array).getPoint());
}
-
+
@Test
public void testDistance() {
EuclideanIntegerPoint e1 = new EuclideanIntegerPoint(new int[] { -3, -2, -1, 0, 1 });
@@ -42,7 +42,7 @@
assertEquals(0.0, e1.distanceFrom(e1), 1.0e-15);
assertEquals(0.0, e2.distanceFrom(e2), 1.0e-15);
}
-
+
@Test
public void testCentroid() {
List<EuclideanIntegerPoint> list = new ArrayList<EuclideanIntegerPoint>();
@@ -54,11 +54,11 @@
assertEquals(2, c.getPoint()[0]);
assertEquals(3, c.getPoint()[1]);
}
-
+
@Test
public void testSerial() {
EuclideanIntegerPoint p = new EuclideanIntegerPoint(new int[] { -3, -2, -1, 0, 1 });
assertEquals(p, TestUtils.serializeAndRecover(p));
}
-
+
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/CovarianceTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/CovarianceTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/CovarianceTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/CovarianceTest.java Sat Sep 5 17:36:48 2009
@@ -24,7 +24,7 @@
import junit.framework.TestCase;
public class CovarianceTest extends TestCase {
-
+
protected final double[] longleyData = new double[] {
60323,83.0,234289,2356,1590,107608,1947,
61122,88.5,259426,2325,1456,108632,1948,
@@ -43,7 +43,7 @@
69331,115.7,518173,4806,2572,127852,1961,
70551,116.9,554894,4007,2827,130081,1962
};
-
+
protected final double[] swissData = new double[] {
80.2,17.0,15,12,9.96,
83.1,45.1,6,9,84.84,
@@ -93,19 +93,19 @@
44.7,46.6,16,29,50.43,
42.8,27.7,22,29,58.33
};
-
-
+
+
/**
* Test Longley dataset against R.
* Data Source: J. Longley (1967) "An Appraisal of Least Squares
* Programs for the Electronic Computer from the Point of View of the User"
* Journal of the American Statistical Association, vol. 62. September,
* pp. 819-841.
- *
+ *
* Data are from NIST:
* http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Longley.dat
*/
- public void testLongly() {
+ public void testLongly() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
RealMatrix covarianceMatrix = new Covariance(matrix).getCovarianceMatrix();
double[] rData = new double[] {
@@ -124,11 +124,11 @@
16240.93333333333, 5.092333333333334e+01, 470977.900000000,
2973.033333333333, 1382.433333333333, 32917.40000000, 22.66666666666667
};
-
+
TestUtils.assertEquals("covariance matrix", createRealMatrix(rData, 7, 7), covarianceMatrix, 10E-9);
}
-
+
/**
* Test R Swiss fertility dataset against R.
* Data Source: R datasets package
@@ -143,10 +143,10 @@
-79.7295097132285, -139.6574005550416, 53.57585568917669, 92.4560592044403, -61.6988297872340,
241.5632030527289, 379.9043755781684, -190.56061054579092, -61.6988297872340, 1739.2945371877890
};
-
+
TestUtils.assertEquals("covariance matrix", createRealMatrix(rData, 5, 5), covarianceMatrix, 10E-13);
}
-
+
/**
* Constant column
*/
@@ -156,8 +156,8 @@
assertEquals(0d, new Covariance().covariance(noVariance, values, true), Double.MIN_VALUE);
assertEquals(0d, new Covariance().covariance(noVariance, noVariance, true), Double.MIN_VALUE);
}
-
-
+
+
/**
* Insufficient data
*/
@@ -178,7 +178,7 @@
// Expected
}
}
-
+
/**
* Verify that diagonal entries are consistent with Variance computation and matrix matches
* column-by-column covariances
@@ -186,18 +186,18 @@
public void testConsistency() {
final RealMatrix matrix = createRealMatrix(swissData, 47, 5);
final RealMatrix covarianceMatrix = new Covariance(matrix).getCovarianceMatrix();
-
+
// Variances on the diagonal
Variance variance = new Variance();
for (int i = 0; i < 5; i++) {
assertEquals(variance.evaluate(matrix.getColumn(i)), covarianceMatrix.getEntry(i,i), 10E-14);
}
-
+
// Symmetry, column-consistency
- assertEquals(covarianceMatrix.getEntry(2, 3),
+ assertEquals(covarianceMatrix.getEntry(2, 3),
new Covariance().covariance(matrix.getColumn(2), matrix.getColumn(3), true), 10E-14);
assertEquals(covarianceMatrix.getEntry(2, 3), covarianceMatrix.getEntry(3, 2), Double.MIN_VALUE);
-
+
// All columns same -> all entries = column variance
RealMatrix repeatedColumns = new Array2DRowRealMatrix(47, 3);
for (int i = 0; i < 3; i++) {
@@ -210,20 +210,20 @@
assertEquals(columnVariance, repeatedCovarianceMatrix.getEntry(i, j), 10E-14);
}
}
-
+
// Check bias-correction defaults
double[][] data = matrix.getData();
- TestUtils.assertEquals("Covariances",
+ TestUtils.assertEquals("Covariances",
covarianceMatrix, new Covariance().computeCovarianceMatrix(data),Double.MIN_VALUE);
- TestUtils.assertEquals("Covariances",
+ TestUtils.assertEquals("Covariances",
covarianceMatrix, new Covariance().computeCovarianceMatrix(data, true),Double.MIN_VALUE);
-
+
double[] x = data[0];
double[] y = data[1];
- assertEquals(new Covariance().covariance(x, y),
- new Covariance().covariance(x, y, true), Double.MIN_VALUE);
+ assertEquals(new Covariance().covariance(x, y),
+ new Covariance().covariance(x, y, true), Double.MIN_VALUE);
}
-
+
protected RealMatrix createRealMatrix(double[] data, int nRows, int nCols) {
double[][] matrixData = new double[nRows][nCols];
int ptr = 0;
@@ -231,6 +231,6 @@
System.arraycopy(data, ptr, matrixData[i], 0, nCols);
ptr += nCols;
}
- return new Array2DRowRealMatrix(matrixData);
+ return new Array2DRowRealMatrix(matrixData);
}
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/PearsonsCorrelationTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/PearsonsCorrelationTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/PearsonsCorrelationTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/PearsonsCorrelationTest.java Sat Sep 5 17:36:48 2009
@@ -25,7 +25,7 @@
import junit.framework.TestCase;
public class PearsonsCorrelationTest extends TestCase {
-
+
protected final double[] longleyData = new double[] {
60323,83.0,234289,2356,1590,107608,1947,
61122,88.5,259426,2325,1456,108632,1948,
@@ -44,7 +44,7 @@
69331,115.7,518173,4806,2572,127852,1961,
70551,116.9,554894,4007,2827,130081,1962
};
-
+
protected final double[] swissData = new double[] {
80.2,17.0,15,12,9.96,
83.1,45.1,6,9,84.84,
@@ -94,14 +94,14 @@
44.7,46.6,16,29,50.43,
42.8,27.7,22,29,58.33
};
-
-
+
+
/**
* Test Longley dataset against R.
*/
- public void testLongly() throws Exception {
+ public void testLongly() throws Exception {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
- PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
+ PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1.000000000000000, 0.9708985250610560, 0.9835516111796693, 0.5024980838759942,
@@ -118,28 +118,28 @@
0.3644162671890320, 1.000000000000000, 0.9939528462329257,
0.971329459192119, 0.9911491900672053, 0.9952734837647849, 0.6682566045621746,
0.4172451498349454, 0.993952846232926, 1.0000000000000000
- };
+ };
TestUtils.assertEquals("correlation matrix", createRealMatrix(rData, 7, 7), correlationMatrix, 10E-15);
-
+
double[] rPvalues = new double[] {
4.38904690369668e-10,
8.36353208910623e-12, 7.8159700933611e-14,
- 0.0472894097790304, 0.01030636128354301, 0.01316878049026582,
+ 0.0472894097790304, 0.01030636128354301, 0.01316878049026582,
0.0749178049642416, 0.06971758330341182, 0.0830166169296545, 0.510948586323452,
- 3.693245043123738e-09, 4.327782576751815e-11, 1.167954621905665e-13, 0.00331028281967516, 0.1652293725106684,
+ 3.693245043123738e-09, 4.327782576751815e-11, 1.167954621905665e-13, 0.00331028281967516, 0.1652293725106684,
3.95834476307755e-10, 1.114663916723657e-13, 1.332267629550188e-15, 0.00466039138541463, 0.1078477071581498, 7.771561172376096e-15
};
RealMatrix rPMatrix = createLowerTriangularRealMatrix(rPvalues, 7);
fillUpper(rPMatrix, 0d);
TestUtils.assertEquals("correlation p values", rPMatrix, corrInstance.getCorrelationPValues(), 10E-15);
}
-
+
/**
* Test R Swiss fertility dataset against R.
*/
public void testSwissFertility() throws Exception {
RealMatrix matrix = createRealMatrix(swissData, 47, 5);
- PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
+ PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1.0000000000000000, 0.3530791836199747, -0.6458827064572875, -0.6637888570350691, 0.4636847006517939,
@@ -149,7 +149,7 @@
0.4636847006517939, 0.4010950530487398, -0.5727418060641666, -0.1538589170909148, 1.0000000000000000
};
TestUtils.assertEquals("correlation matrix", createRealMatrix(rData, 5, 5), correlationMatrix, 10E-15);
-
+
double[] rPvalues = new double[] {
0.01491720061472623,
9.45043734069043e-07, 9.95151527133974e-08,
@@ -160,7 +160,7 @@
fillUpper(rPMatrix, 0d);
TestUtils.assertEquals("correlation p values", rPMatrix, corrInstance.getCorrelationPValues(), 10E-15);
}
-
+
/**
* Constant column
*/
@@ -169,12 +169,12 @@
double[] values = new double[] {1, 2, 3, 4};
assertTrue(Double.isNaN(new PearsonsCorrelation().correlation(noVariance, values)));
}
-
-
+
+
/**
* Insufficient data
*/
-
+
public void testInsufficientData() {
double[] one = new double[] {1};
double[] two = new double[] {2};
@@ -192,7 +192,7 @@
// Expected
}
}
-
+
/**
* Verify that direct t-tests using standard error estimates are consistent
* with reported p-values
@@ -200,7 +200,7 @@
public void testStdErrorConsistency() throws Exception {
TDistribution tDistribution = new TDistributionImpl(45);
RealMatrix matrix = createRealMatrix(swissData, 47, 5);
- PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
+ PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
RealMatrix rValues = corrInstance.getCorrelationMatrix();
RealMatrix pValues = corrInstance.getCorrelationPValues();
RealMatrix stdErrors = corrInstance.getCorrelationStandardErrors();
@@ -212,14 +212,14 @@
}
}
}
-
+
/**
* Verify that creating correlation from covariance gives same results as
* direct computation from the original matrix
*/
public void testCovarianceConsistency() throws Exception {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
- PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
+ PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
Covariance covInstance = new Covariance(matrix);
PearsonsCorrelation corrFromCovInstance = new PearsonsCorrelation(covInstance);
TestUtils.assertEquals("correlation values", corrInstance.getCorrelationMatrix(),
@@ -228,8 +228,8 @@
corrFromCovInstance.getCorrelationPValues(), 10E-15);
TestUtils.assertEquals("standard errors", corrInstance.getCorrelationStandardErrors(),
corrFromCovInstance.getCorrelationStandardErrors(), 10E-15);
-
- PearsonsCorrelation corrFromCovInstance2 =
+
+ PearsonsCorrelation corrFromCovInstance2 =
new PearsonsCorrelation(covInstance.getCovarianceMatrix(), 16);
TestUtils.assertEquals("correlation values", corrInstance.getCorrelationMatrix(),
corrFromCovInstance2.getCorrelationMatrix(), 10E-15);
@@ -238,20 +238,20 @@
TestUtils.assertEquals("standard errors", corrInstance.getCorrelationStandardErrors(),
corrFromCovInstance2.getCorrelationStandardErrors(), 10E-15);
}
-
-
+
+
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
- PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
+ PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
- assertEquals(new PearsonsCorrelation().correlation(x, y),
+ assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
-
+
protected RealMatrix createRealMatrix(double[] data, int nRows, int nCols) {
double[][] matrixData = new double[nRows][nCols];
int ptr = 0;
@@ -259,9 +259,9 @@
System.arraycopy(data, ptr, matrixData[i], 0, nCols);
ptr += nCols;
}
- return new BlockRealMatrix(matrixData);
+ return new BlockRealMatrix(matrixData);
}
-
+
protected RealMatrix createLowerTriangularRealMatrix(double[] data, int dimension) {
int ptr = 0;
RealMatrix result = new BlockRealMatrix(dimension, dimension);
@@ -273,7 +273,7 @@
}
return result;
}
-
+
protected void fillUpper(RealMatrix matrix, double diagonalValue) {
int dimension = matrix.getColumnDimension();
for (int i = 0; i < dimension; i++) {
@@ -281,6 +281,6 @@
for (int j = i+1; j < dimension; j++) {
matrix.setEntry(i, j, matrix.getEntry(j, i));
}
- }
+ }
}
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/SpearmansRankCorrelationTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/SpearmansRankCorrelationTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/SpearmansRankCorrelationTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/correlation/SpearmansRankCorrelationTest.java Sat Sep 5 17:36:48 2009
@@ -22,7 +22,7 @@
/**
* Test cases for Spearman's rank correlation
- *
+ *
* @since 2.0
* @version $Revision$ $Date$
*/
@@ -37,14 +37,14 @@
protected void tearDown() throws Exception {
super.tearDown();
}
-
+
/**
* Test Longley dataset against R.
*/
@Override
- public void testLongly() throws Exception {
+ public void testLongly() throws Exception {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
- SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
+ SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1, 0.982352941176471, 0.985294117647059, 0.564705882352941, 0.2264705882352941, 0.976470588235294,
@@ -55,16 +55,16 @@
0.2205882352941176, 0.2235294117647059, -0.3411764705882353, 1, 0.2264705882352941, 0.2264705882352941,
0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1,
0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1
- };
+ };
TestUtils.assertEquals("Spearman's correlation matrix", createRealMatrix(rData, 7, 7), correlationMatrix, 10E-15);
}
-
+
/**
* Test R swiss fertility dataset.
*/
- public void testSwiss() throws Exception {
+ public void testSwiss() throws Exception {
RealMatrix matrix = createRealMatrix(swissData, 47, 5);
- SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
+ SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1, 0.2426642769364176, -0.660902996352354, -0.443257690360988, 0.4136455623012432,
@@ -72,10 +72,10 @@
-0.660902996352354, -0.598859938748963, 1, 0.674603831406147, -0.4750575257171745,
-0.443257690360988, -0.650463814145816, 0.674603831406147, 1, -0.1444163088302244,
0.4136455623012432, 0.2886878090882852, -0.4750575257171745, -0.1444163088302244, 1
- };
+ };
TestUtils.assertEquals("Spearman's correlation matrix", createRealMatrix(rData, 5, 5), correlationMatrix, 10E-15);
}
-
+
/**
* Constant column
*/
@@ -85,10 +85,10 @@
double[] values = new double[] {1, 2, 3, 4};
assertTrue(Double.isNaN(new SpearmansCorrelation().correlation(noVariance, values)));
}
-
+
/**
* Insufficient data
- */
+ */
@Override
public void testInsufficientData() {
double[] one = new double[] {1};
@@ -107,24 +107,24 @@
// Expected
}
}
-
+
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
- SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
+ SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
- assertEquals(new SpearmansCorrelation().correlation(x, y),
+ assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
-
+
// Not relevant here
@Override
public void testStdErrorConsistency() throws Exception {}
@Override
public void testCovarianceConsistency() throws Exception {}
-
+
}