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From pste...@apache.org
Subject svn commit: r811685 [22/24] - 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...
Date Sat, 05 Sep 2009 17:37:05 GMT
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/CertifiedDataAbstractTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/CertifiedDataAbstractTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/CertifiedDataAbstractTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/CertifiedDataAbstractTest.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.
@@ -36,11 +36,11 @@
  * @version $Revision$ $Date$
  */
 public abstract class CertifiedDataAbstractTest extends TestCase {
-    
+
     private DescriptiveStatistics descriptives;
-    
+
     private SummaryStatistics summaries;
-    
+
     private Map<String, Double> certifiedValues;
 
     @Override
@@ -48,7 +48,7 @@
         descriptives = new DescriptiveStatistics();
         summaries = new SummaryStatistics();
         certifiedValues = new HashMap<String, Double>();
-        
+
         loadData();
     }
 
@@ -58,12 +58,12 @@
         try {
             URL resourceURL = getClass().getClassLoader().getResource(getResourceName());
             in = new BufferedReader(new InputStreamReader(resourceURL.openStream()));
-            
+
             String line = in.readLine();
             while (line != null) {
-                
-                /* this call to StringUtils did little for the 
-                 * following conditional structure 
+
+                /* this call to StringUtils did little for the
+                 * following conditional structure
                  */
                 line = line.trim();
 
@@ -102,14 +102,14 @@
     protected void tearDown() throws Exception {
         descriptives.clear();
         descriptives = null;
-        
+
         summaries.clear();
         summaries = null;
-        
+
         certifiedValues.clear();
         certifiedValues = null;
     }
-    
+
     public void testCertifiedValues() {
         for (String name : certifiedValues.keySet()) {
             Double expectedValue = certifiedValues.get(name);
@@ -129,12 +129,12 @@
             }
         }
     }
-    
-    
+
+
     protected Double getProperty(Object bean, String name) {
         try {
             // Get the value of prop
-            String prop = "get" + name.substring(0,1).toUpperCase() + name.substring(1); 
+            String prop = "get" + name.substring(0,1).toUpperCase() + name.substring(1);
             Method meth = bean.getClass().getMethod(prop, new Class[0]);
             Object property = meth.invoke(bean, new Object[0]);
             if (meth.getReturnType().equals(Double.TYPE)) {

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LewTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LewTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LewTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LewTest.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.

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LotteryTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LotteryTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LotteryTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/data/LotteryTest.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.

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AbstractUnivariateStatisticTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AbstractUnivariateStatisticTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AbstractUnivariateStatisticTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AbstractUnivariateStatisticTest.java Sat Sep  5 17:36:48 2009
@@ -23,38 +23,38 @@
 import org.apache.commons.math.stat.descriptive.moment.Mean;
 
 /**
- * Tests for AbstractUnivariateStatistic 
+ * Tests for AbstractUnivariateStatistic
  *
  * @version $Revision$ $Date$
  */
 public class AbstractUnivariateStatisticTest extends TestCase {
-    
+
     public AbstractUnivariateStatisticTest(String name) {
         super(name);
     }
-    
+
     public static Test suite() {
         TestSuite suite = new TestSuite(AbstractUnivariateStatisticTest.class);
         suite.setName("AbstractUnivariateStatistic Tests");
         return suite;
     }
-    
+
     protected double[] testArray = {0, 1, 2, 3, 4, 5};
     protected double[] testWeightsArray = {0.3, 0.2, 1.3, 1.1, 1.0, 1.8};
     protected double[] testNegativeWeightsArray = {-0.3, 0.2, -1.3, 1.1, 1.0, 1.8};
     protected double[] nullArray = null;
     protected double[] singletonArray = {0};
     protected Mean testStatistic = new Mean();
-    
+
     public void testTestPositive() {
         for (int j = 0; j < 6; j++) {
             for (int i = 1; i < (7 - j); i++) {
                 assertTrue(testStatistic.test(testArray, 0, i));
-            }  
+            }
         }
         assertTrue(testStatistic.test(singletonArray, 0, 1));
     }
-    
+
     public void testTestNegative() {
         assertFalse(testStatistic.test(singletonArray, 0, 0));
         assertFalse(testStatistic.test(testArray, 0, 0));

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AggregateSummaryStatisticsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AggregateSummaryStatisticsTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AggregateSummaryStatisticsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/AggregateSummaryStatisticsTest.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.
@@ -34,7 +34,7 @@
  *
  */
 public class AggregateSummaryStatisticsTest extends TestCase {
-    
+
     /**
      * Creates and returns a {@code Test} representing all the test cases in this
      * class
@@ -46,7 +46,7 @@
         suite.setName("AggregateSummaryStatistics tests");
         return suite;
     }
-    
+
     /**
      * Tests the standard aggregation behavior
      */
@@ -54,11 +54,11 @@
         AggregateSummaryStatistics aggregate = new AggregateSummaryStatistics();
         SummaryStatistics setOneStats = aggregate.createContributingStatistics();
         SummaryStatistics setTwoStats = aggregate.createContributingStatistics();
-        
+
         assertNotNull("The set one contributing stats are null", setOneStats);
         assertNotNull("The set two contributing stats are null", setTwoStats);
         assertNotSame("Contributing stats objects are the same", setOneStats, setTwoStats);
-        
+
         setOneStats.addValue(2);
         setOneStats.addValue(3);
         setOneStats.addValue(5);
@@ -66,93 +66,93 @@
         setOneStats.addValue(11);
         assertEquals("Wrong number of set one values", 5, setOneStats.getN());
         assertEquals("Wrong sum of set one values", 28.0, setOneStats.getSum());
-        
+
         setTwoStats.addValue(2);
         setTwoStats.addValue(4);
         setTwoStats.addValue(8);
         assertEquals("Wrong number of set two values", 3, setTwoStats.getN());
         assertEquals("Wrong sum of set two values", 14.0, setTwoStats.getSum());
-        
+
         assertEquals("Wrong number of aggregate values", 8, aggregate.getN());
         assertEquals("Wrong aggregate sum", 42.0, aggregate.getSum());
     }
-    
+
     /**
      * Verify that aggregating over a partition gives the same results
      * as direct computation.
-     * 
+     *
      *  1) Randomly generate a dataset of 10-100 values
      *     from [-100, 100]
      *  2) Divide the dataset it into 2-5 partitions
      *  3) Create an AggregateSummaryStatistic and ContributingStatistics
-     *     for each partition 
+     *     for each partition
      *  4) Compare results from the AggregateSummaryStatistic with values
-     *     returned by a single SummaryStatistics instance that is provided 
+     *     returned by a single SummaryStatistics instance that is provided
      *     the full dataset
      */
     public void testAggregationConsistency() throws Exception {
-        
+
         // Generate a random sample and random partition
         double[] totalSample = generateSample();
         double[][] subSamples = generatePartition(totalSample);
         int nSamples = subSamples.length;
-        
+
         // Create aggregator and total stats for comparison
         AggregateSummaryStatistics aggregate = new AggregateSummaryStatistics();
         SummaryStatistics totalStats = new SummaryStatistics();
-        
+
         // Create array of component stats
         SummaryStatistics componentStats[] = new SummaryStatistics[nSamples];
-        
+
         for (int i = 0; i < nSamples; i++) {
-            
+
             // Make componentStats[i] a contributing statistic to aggregate
             componentStats[i] = aggregate.createContributingStatistics();
-            
+
             // Add values from subsample
             for (int j = 0; j < subSamples[i].length; j++) {
                 componentStats[i].addValue(subSamples[i][j]);
             }
         }
-        
+
         // Compute totalStats directly
         for (int i = 0; i < totalSample.length; i++) {
             totalStats.addValue(totalSample[i]);
         }
-        
+
         /*
          * Compare statistics in totalStats with aggregate.
          * Note that guaranteed success of this comparison depends on the
          * fact that <aggregate> gets values in exactly the same order
-         * as <totalStats>. 
-         *  
+         * as <totalStats>.
+         *
          */
-        assertEquals(totalStats.getSummary(), aggregate.getSummary());  
-        
+        assertEquals(totalStats.getSummary(), aggregate.getSummary());
+
     }
-    
+
     /**
      * Test aggregate function by randomly generating a dataset of 10-100 values
      * from [-100, 100], dividing it into 2-5 partitions, computing stats for each
      * partition and comparing the result of aggregate(...) applied to the collection
      * of per-partition SummaryStatistics with a single SummaryStatistics computed
      * over the full sample.
-     * 
+     *
      * @throws Exception
      */
     public void testAggregate() throws Exception {
-        
+
         // Generate a random sample and random partition
         double[] totalSample = generateSample();
         double[][] subSamples = generatePartition(totalSample);
         int nSamples = subSamples.length;
-       
+
         // Compute combined stats directly
         SummaryStatistics totalStats = new SummaryStatistics();
         for (int i = 0; i < totalSample.length; i++) {
             totalStats.addValue(totalSample[i]);
         }
-        
+
         // Now compute subsample stats individually and aggregate
         SummaryStatistics[] subSampleStats = new SummaryStatistics[nSamples];
         for (int i = 0; i < nSamples; i++) {
@@ -160,28 +160,28 @@
         }
         Collection<SummaryStatistics> aggregate = new ArrayList<SummaryStatistics>();
         for (int i = 0; i < nSamples; i++) {
-            for (int j = 0; j < subSamples[i].length; j++) { 
+            for (int j = 0; j < subSamples[i].length; j++) {
                 subSampleStats[i].addValue(subSamples[i][j]);
             }
             aggregate.add(subSampleStats[i]);
         }
-        
+
         // Compare values
         StatisticalSummary aggregatedStats = AggregateSummaryStatistics.aggregate(aggregate);
         assertEquals(totalStats.getSummary(), aggregatedStats, 10E-12);
     }
-    
-    
+
+
     public void testAggregateDegenerate() throws Exception {
         double[] totalSample = {1, 2, 3, 4, 5};
         double[][] subSamples = {{1}, {2}, {3}, {4}, {5}};
-        
+
         // Compute combined stats directly
         SummaryStatistics totalStats = new SummaryStatistics();
         for (int i = 0; i < totalSample.length; i++) {
             totalStats.addValue(totalSample[i]);
         }
-        
+
         // Now compute subsample stats individually and aggregate
         SummaryStatistics[] subSampleStats = new SummaryStatistics[5];
         for (int i = 0; i < 5; i++) {
@@ -189,27 +189,27 @@
         }
         Collection<SummaryStatistics> aggregate = new ArrayList<SummaryStatistics>();
         for (int i = 0; i < 5; i++) {
-            for (int j = 0; j < subSamples[i].length; j++) { 
+            for (int j = 0; j < subSamples[i].length; j++) {
                 subSampleStats[i].addValue(subSamples[i][j]);
             }
             aggregate.add(subSampleStats[i]);
         }
-        
+
         // Compare values
         StatisticalSummaryValues aggregatedStats = AggregateSummaryStatistics.aggregate(aggregate);
         assertEquals(totalStats.getSummary(), aggregatedStats, 10E-12);
     }
-    
+
     public void testAggregateSpecialValues() throws Exception {
         double[] totalSample = {Double.POSITIVE_INFINITY, 2, 3, Double.NaN, 5};
         double[][] subSamples = {{Double.POSITIVE_INFINITY, 2}, {3}, {Double.NaN}, {5}};
-        
+
         // Compute combined stats directly
         SummaryStatistics totalStats = new SummaryStatistics();
         for (int i = 0; i < totalSample.length; i++) {
             totalStats.addValue(totalSample[i]);
         }
-        
+
         // Now compute subsample stats individually and aggregate
         SummaryStatistics[] subSampleStats = new SummaryStatistics[5];
         for (int i = 0; i < 4; i++) {
@@ -217,18 +217,18 @@
         }
         Collection<SummaryStatistics> aggregate = new ArrayList<SummaryStatistics>();
         for (int i = 0; i < 4; i++) {
-            for (int j = 0; j < subSamples[i].length; j++) { 
+            for (int j = 0; j < subSamples[i].length; j++) {
                 subSampleStats[i].addValue(subSamples[i][j]);
             }
             aggregate.add(subSampleStats[i]);
         }
-        
+
         // Compare values
         StatisticalSummaryValues aggregatedStats = AggregateSummaryStatistics.aggregate(aggregate);
         assertEquals(totalStats.getSummary(), aggregatedStats, 10E-12);
-        
+
     }
-    
+
     /**
      * Verifies that a StatisticalSummary and a StatisticalSummaryValues are equal up
      * to delta, with NaNs, infinities returned in the same spots. For max, min, n, values
@@ -244,12 +244,12 @@
         TestUtils.assertEquals(expected.getVariance(), observed.getVariance(), delta);
     }
 
-    
+
     /**
      * Generates a random sample of double values.
-     * Sample size is random, between 10 and 100 and values are 
+     * Sample size is random, between 10 and 100 and values are
      * uniformly distributed over [-100, 100].
-     * 
+     *
      * @return array of random double values
      */
     private double[] generateSample() {
@@ -259,13 +259,13 @@
         for (int i = 0; i < out.length; i++) {
             out[i] = randomData.nextUniform(-100, 100);
         }
-        return out;     
+        return out;
     }
-    
+
     /**
      * Generates a partition of <sample> into up to 5 sequentially selected
      * subsamples with randomly selected partition points.
-     * 
+     *
      * @param sample array to partition
      * @return rectangular array with rows = subsamples
      */
@@ -300,5 +300,5 @@
             return out;
         }
     }
-    
+
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/DescriptiveStatisticsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/DescriptiveStatisticsTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/DescriptiveStatisticsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/DescriptiveStatisticsTest.java Sat Sep  5 17:36:48 2009
@@ -24,7 +24,7 @@
 
 /**
  * Test cases for the DescriptiveStatistics class.
- * 
+ *
  * @version $Revision$ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
  *          2007) $
  */
@@ -53,7 +53,7 @@
         stats.setMeanImpl(new deepMean());
         assertEquals(42, stats.getMean(), 1E-10);
     }
-    
+
     public void testCopy() {
         DescriptiveStatistics stats = createDescriptiveStatistics();
         stats.addValue(1);
@@ -65,7 +65,7 @@
         copy = stats.copy();
         assertEquals(42, copy.getMean(), 1E-10);
     }
-    
+
     public void testWindowSize() {
         DescriptiveStatistics stats = createDescriptiveStatistics();
         stats.setWindowSize(300);
@@ -89,7 +89,7 @@
         int refSum2 = refSum - (50 * 51) / 2;
         assertEquals(refSum2 / 50.0, stats.getMean(), 1E-10);
     }
-    
+
     public void testGetValues() {
         DescriptiveStatistics stats = createDescriptiveStatistics();
         for (int i = 100; i > 0; --i) {
@@ -107,7 +107,7 @@
         }
         assertEquals(12.0, stats.getElement(88), 1.0e-10);
     }
-    
+
     public void testToString() {
         DescriptiveStatistics stats = createDescriptiveStatistics();
         stats.addValue(1);
@@ -161,25 +161,25 @@
         assertEquals(reference.getGeometricMean(), shuffled.getSumsq(), 1.0e-10);
 
     }
-    
+
     public void testPercentileSetter() throws Exception {
         DescriptiveStatistics stats = createDescriptiveStatistics();
         stats.addValue(1);
         stats.addValue(2);
         stats.addValue(3);
         assertEquals(2, stats.getPercentile(50.0), 1E-10);
-        
+
         // Inject wrapped Percentile impl
         stats.setPercentileImpl(new goodPercentile());
         assertEquals(2, stats.getPercentile(50.0), 1E-10);
-        
+
         // Try "new math" impl
         stats.setPercentileImpl(new subPercentile());
         assertEquals(10.0, stats.getPercentile(10.0), 1E-10);
-        
+
         // Try to set bad impl
         try {
-            stats.setPercentileImpl(new badPercentile()); 
+            stats.setPercentileImpl(new badPercentile());
             fail("Expecting IllegalArgumentException");
         } catch (IllegalArgumentException ex) {
             // expected
@@ -225,11 +225,11 @@
         assertTrue(MathUtils.equals(mean3, dstat.getMean()));
 
     }
-    
+
     // Test UnivariateStatistics impls for setter injection tests
-    
+
     /**
-     * A new way to compute the mean 
+     * A new way to compute the mean
      */
     static class deepMean implements UnivariateStatistic {
 
@@ -239,12 +239,12 @@
 
         public double evaluate(double[] values) {
             return 42;
-        }  
+        }
         public UnivariateStatistic copy() {
             return new deepMean();
         }
     }
-    
+
     /**
      * Test percentile implementation - wraps a Percentile
      */
@@ -258,14 +258,14 @@
         }
         public double evaluate(double[] values) {
             return percentile.evaluate(values);
-        }  
+        }
         public UnivariateStatistic copy() {
             goodPercentile result = new goodPercentile();
             result.setQuantile(percentile.getQuantile());
             return result;
         }
     }
-    
+
     /**
      * Test percentile subclass - another "new math" impl
      * Always returns currently set quantile
@@ -278,7 +278,7 @@
         @Override
         public double evaluate(double[] values) {
             return getQuantile();
-        }  
+        }
         private static final long serialVersionUID = 8040701391045914979L;
         @Override
         public Percentile copy() {
@@ -286,7 +286,7 @@
             return result;
         }
     }
-    
+
     /**
      * "Bad" test percentile implementation - no setQuantile
      */
@@ -302,5 +302,5 @@
             return new badPercentile();
         }
     }
-    
+
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/InteractionTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/InteractionTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/InteractionTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/InteractionTest.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.
@@ -67,7 +67,7 @@
 
 
     public void testInteraction() {
-        
+
         FourthMoment m4 = new FourthMoment();
         Mean m = new Mean(m4);
         Variance v = new Variance(m4);
@@ -77,7 +77,7 @@
         for (int i = 0; i < testArray.length; i++){
             m4.increment(testArray[i]);
         }
-        
+
         assertEquals(mean,m.getResult(),tolerance);
         assertEquals(var,v.getResult(),tolerance);
         assertEquals(skew ,s.getResult(),tolerance);

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImpl.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImpl.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImpl.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImpl.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 @@
 
     /** Serializable version identifier */
     private static final long serialVersionUID = -8837442489133392138L;
-    
+
     /**
      * Holds a reference to a list - GENERICs are going to make
      * our lives easier here as we could only accept List<Number>
@@ -49,7 +49,7 @@
     public ListUnivariateImpl(){
         this(new ArrayList<Object>());
     }
-    
+
     /**
      * Construct a ListUnivariate with a specific List.
      * @param list The list that will back this DescriptiveStatistics
@@ -57,7 +57,7 @@
     public ListUnivariateImpl(List<Object> list) {
         this(list, new DefaultTransformer());
     }
-    
+
     /**
      * Construct a ListUnivariate with a specific List.
      * @param list The list that will back this DescriptiveStatistics
@@ -109,13 +109,13 @@
             calcIndex = (list.size() - windowSize) + index;
         }
 
-        
+
         try {
             value = transformer.transform(list.get(calcIndex));
         } catch (MathException e) {
             e.printStackTrace();
         }
-        
+
         return value;
     }
 
@@ -141,9 +141,9 @@
     public void addValue(double v) {
         list.add(Double.valueOf(v));
     }
-    
+
     /**
-     * Adds an object to this list. 
+     * Adds an object to this list.
      * @param o Object to add to the list
      */
     public void addObject(Object o) {
@@ -159,7 +159,7 @@
     public void clear() {
         list.clear();
     }
-    
+
     /**
      * Apply the given statistic to this univariate collection.
      * @param stat the statistic to apply
@@ -174,7 +174,7 @@
         }
         return Double.NaN;
     }
-    
+
     /**
      * Access the number transformer.
      * @return the number transformer.
@@ -190,12 +190,12 @@
     public void setTransformer(NumberTransformer transformer) {
         this.transformer = transformer;
     }
-    
+
     /** {@inheritDoc} */
     @Override
     public synchronized void setWindowSize(int windowSize) {
         this.windowSize = windowSize;
-        //Discard elements from the front of the list if the windowSize is less than 
+        //Discard elements from the front of the list if the windowSize is less than
         // the size of the list.
         int extra = list.size() - windowSize;
         for (int i = 0; i < extra; i++) {
@@ -209,4 +209,4 @@
         return windowSize;
     }
 
-}
\ No newline at end of file
+}

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImplTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImplTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImplTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/ListUnivariateImplTest.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.
@@ -32,7 +32,7 @@
  */
 
 public final class ListUnivariateImplTest extends TestCase {
-    
+
     private double one = 1;
     private float two = 2;
     private int three = 3;
@@ -46,22 +46,22 @@
     private double min = 1;
     private double max = 3;
     private double tolerance = 10E-15;
-    
+
     public ListUnivariateImplTest(String name) {
         super(name);
     }
-    
+
     public static Test suite() {
         TestSuite suite = new TestSuite(ListUnivariateImplTest.class);
         suite.setName("Frequency Tests");
         return suite;
     }
-    
+
     /** test stats */
     public void testStats() {
         List<Object> externalList = new ArrayList<Object>();
-        
-        DescriptiveStatistics u = new ListUnivariateImpl( externalList ); 
+
+        DescriptiveStatistics u = new ListUnivariateImpl( externalList );
 
         assertEquals("total count",0,u.getN(),tolerance);
         u.addValue(one);
@@ -77,14 +77,14 @@
         assertEquals("min",min,u.getMin(),tolerance);
         assertEquals("max",max,u.getMax(),tolerance);
         u.clear();
-        assertEquals("total count",0,u.getN(),tolerance);    
-    }     
-    
+        assertEquals("total count",0,u.getN(),tolerance);
+    }
+
     public void testN0andN1Conditions() throws Exception {
         List<Object> list = new ArrayList<Object>();
-        
+
         DescriptiveStatistics u = new ListUnivariateImpl( list );
-                
+
         assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
         assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
         assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
@@ -93,18 +93,18 @@
 
         assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
         assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
-        assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);  
+        assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
     }
-    
+
     public void testSkewAndKurtosis() {
         DescriptiveStatistics u = new DescriptiveStatistics();
-        
+
         double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
                                              9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
         for( int i = 0; i < testArray.length; i++) {
             u.addValue( testArray[i]);
         }
-        
+
         assertEquals("mean", 12.40455, u.getMean(), 0.0001);
         assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
         assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
@@ -114,7 +114,7 @@
     public void testProductAndGeometricMean() throws Exception {
         ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<Object>());
         u.setWindowSize(10);
-                
+
         u.addValue( 1.0 );
         u.addValue( 2.0 );
         u.addValue( 3.0 );
@@ -128,26 +128,26 @@
             u.addValue( i + 2 );
         }
         // Values should be (2,3,4,5,6,7,8,9,10,11)
-        
+
         assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
 
 
     }
-    
+
     /** test stats */
     public void testSerialization() {
-        
+
         DescriptiveStatistics u = new ListUnivariateImpl();
-        
+
         assertEquals("total count",0,u.getN(),tolerance);
         u.addValue(one);
         u.addValue(two);
-        
-        DescriptiveStatistics u2 = (DescriptiveStatistics)TestUtils.serializeAndRecover(u); 
- 
+
+        DescriptiveStatistics u2 = (DescriptiveStatistics)TestUtils.serializeAndRecover(u);
+
         u2.addValue(two);
         u2.addValue(three);
-        
+
         assertEquals("N",n,u2.getN(),tolerance);
         assertEquals("sum",sum,u2.getSum(),tolerance);
         assertEquals("sumsq",sumSq,u2.getSumsq(),tolerance);
@@ -158,7 +158,7 @@
         assertEquals("max",max,u2.getMax(),tolerance);
 
         u2.clear();
-        assertEquals("total count",0,u2.getN(),tolerance);    
-    }       
+        assertEquals("total count",0,u2.getN(),tolerance);
+    }
 }
 

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MixedListUnivariateImplTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MixedListUnivariateImplTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MixedListUnivariateImplTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MixedListUnivariateImplTest.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.
@@ -48,7 +48,7 @@
     private double tolerance = 10E-15;
 
     private TransformerMap transformers = new TransformerMap();
-    
+
     public MixedListUnivariateImplTest(String name) {
         super(name);
         transformers = new TransformerMap();
@@ -106,7 +106,7 @@
         assertTrue(
             "Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean() ,
             u.getMean() == one);
-            
+
         assertTrue(
             "StdDev of n = 1 set should be zero, instead it is: "
                 + u.getStandardDeviation(),

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatisticsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatisticsTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatisticsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatisticsTest.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.
@@ -38,7 +38,7 @@
     public MultivariateSummaryStatisticsTest(String name) {
         super(name);
     }
-    
+
     public static Test suite() {
         TestSuite suite = new TestSuite(MultivariateSummaryStatisticsTest.class);
         suite.setName("MultivariateSummaryStatistics tests");
@@ -73,7 +73,7 @@
         assertEquals(3, u.getMean()[1], 1E-14);
         assertEquals(2, u.getDimension());
     }
-    
+
     public void testSetterIllegalState() throws Exception {
         MultivariateSummaryStatistics u = createMultivariateSummaryStatistics(2, true);
         u.addValue(new double[] { 1, 2 });
@@ -139,12 +139,12 @@
         TestUtils.assertEquals(reference.getGeometricMean(), shuffled.getSumLog(),        1.0e-10);
 
     }
-    
+
     /**
      * Bogus mean implementation to test setter injection.
      * Returns the sum instead of the mean.
      */
-    static class sumMean implements StorelessUnivariateStatistic {   
+    static class sumMean implements StorelessUnivariateStatistic {
         private double sum = 0;
         private long n = 0;
         public double evaluate(double[] values, int begin, int length) {
@@ -154,7 +154,7 @@
             return 0;
         }
         public void clear() {
-          sum = 0; 
+          sum = 0;
           n = 0;
         }
         public long getN() {
@@ -170,7 +170,7 @@
         public void incrementAll(double[] values, int start, int length) {
         }
         public void incrementAll(double[] values) {
-        }   
+        }
         public StorelessUnivariateStatistic copy() {
             return new sumMean();
         }
@@ -216,8 +216,8 @@
         assertEquals(2.0 / 3.0, u.getCovariance().getEntry(1, 0), 1.0e-10);
         assertEquals(2.0 / 3.0, u.getCovariance().getEntry(1, 1), 1.0e-10);
         u.clear();
-        assertEquals(0, u.getN());    
-    }     
+        assertEquals(0, u.getN());
+    }
 
     public void testN0andN1Conditions() throws Exception {
         MultivariateSummaryStatistics u = createMultivariateSummaryStatistics(1, true);
@@ -230,7 +230,7 @@
         assertEquals(1.0, u.getGeometricMean()[0], 1.0e-10);
         assertEquals(0.0, u.getStandardDeviation()[0], 1.0e-10);
 
-        /* n=2 */               
+        /* n=2 */
         u.addValue(new double[] { 2 });
         assertTrue(u.getStandardDeviation()[0] > 0);
 
@@ -238,15 +238,15 @@
 
     public void testNaNContracts() throws DimensionMismatchException {
         MultivariateSummaryStatistics u = createMultivariateSummaryStatistics(1, true);
-        assertTrue(Double.isNaN(u.getMean()[0])); 
-        assertTrue(Double.isNaN(u.getMin()[0])); 
-        assertTrue(Double.isNaN(u.getStandardDeviation()[0])); 
+        assertTrue(Double.isNaN(u.getMean()[0]));
+        assertTrue(Double.isNaN(u.getMin()[0]));
+        assertTrue(Double.isNaN(u.getStandardDeviation()[0]));
         assertTrue(Double.isNaN(u.getGeometricMean()[0]));
 
         u.addValue(new double[] { 1.0 });
-        assertFalse(Double.isNaN(u.getMean()[0])); 
-        assertFalse(Double.isNaN(u.getMin()[0])); 
-        assertFalse(Double.isNaN(u.getStandardDeviation()[0])); 
+        assertFalse(Double.isNaN(u.getMean()[0]));
+        assertFalse(Double.isNaN(u.getMin()[0]));
+        assertFalse(Double.isNaN(u.getStandardDeviation()[0]));
         assertFalse(Double.isNaN(u.getGeometricMean()[0]));
 
     }
@@ -302,7 +302,7 @@
         t.addValue(new double[] { 5d, 1d });
         assertTrue(t.equals(u));
         assertTrue(u.equals(t));
-        assertEquals(u.hashCode(), t.hashCode());   
+        assertEquals(u.hashCode(), t.hashCode());
 
         // Clear and make sure summaries are indistinguishable from empty summary
         u.clear();

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValuesTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValuesTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValuesTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValuesTest.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.
@@ -29,25 +29,25 @@
  */
 
 public final class StatisticalSummaryValuesTest extends TestCase {
-    
-    
+
+
     public StatisticalSummaryValuesTest(String name) {
         super(name);
     }
-    
+
     public static Test suite() {
         TestSuite suite = new TestSuite(StatisticalSummaryValuesTest.class);
         suite.setName("StatisticalSummaryValues Tests");
         return suite;
     }
-      
+
     public void testSerialization() {
         StatisticalSummaryValues u = new StatisticalSummaryValues(1, 2, 3, 4, 5, 6);
-        TestUtils.checkSerializedEquality(u); 
+        TestUtils.checkSerializedEquality(u);
         StatisticalSummaryValues t = (StatisticalSummaryValues) TestUtils.serializeAndRecover(u);
         verifyEquality(u, t);
     }
-    
+
     public void testEqualsAndHashCode() {
         StatisticalSummaryValues u  = new StatisticalSummaryValues(1, 2, 3, 4, 5, 6);
         StatisticalSummaryValues t = null;
@@ -57,13 +57,13 @@
         t = new StatisticalSummaryValues(1, 2, 3, 4, 5, 6);
         assertTrue("instances with same data should be equal", t.equals(u));
         assertEquals("hash code", u.hashCode(), t.hashCode());
-        
+
         u = new StatisticalSummaryValues(Double.NaN, 2, 3, 4, 5, 6);
         t = new StatisticalSummaryValues(1, Double.NaN, 3, 4, 5, 6);
-        assertFalse("instances based on different data should be different", 
+        assertFalse("instances based on different data should be different",
                 (u.equals(t) ||t.equals(u)));
     }
-    
+
     private void verifyEquality(StatisticalSummaryValues s, StatisticalSummaryValues u) {
         assertEquals("N",s.getN(),u.getN());
         TestUtils.assertEquals("sum",s.getSum(),u.getSum(), 0);
@@ -71,6 +71,6 @@
         TestUtils.assertEquals("std",s.getStandardDeviation(),u.getStandardDeviation(), 0);
         TestUtils.assertEquals("mean",s.getMean(),u.getMean(), 0);
         TestUtils.assertEquals("min",s.getMin(),u.getMin(), 0);
-        TestUtils.assertEquals("max",s.getMax(),u.getMax(), 0);   
+        TestUtils.assertEquals("max",s.getMax(),u.getMax(), 0);
     }
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatisticAbstractTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatisticAbstractTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatisticAbstractTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatisticAbstractTest.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.
@@ -29,7 +29,7 @@
     public StorelessUnivariateStatisticAbstractTest(String name) {
         super(name);
     }
-    
+
     /** Small sample arrays */
     protected double[][] smallSamples = {{}, {1}, {1,2}, {1,2,3}, {1,2,3,4}};
 
@@ -40,32 +40,32 @@
     /**Expected value for  the testArray defined in UnivariateStatisticAbstractTest */
     @Override
     public abstract double expectedValue();
-    
-    /** 
-     *  Verifies that increment() and incrementAll work properly. 
+
+    /**
+     *  Verifies that increment() and incrementAll work properly.
      */
     public void testIncrementation() throws Exception {
 
         StorelessUnivariateStatistic statistic =
             (StorelessUnivariateStatistic) getUnivariateStatistic();
-        
+
         // Add testArray one value at a time and check result
         for (int i = 0; i < testArray.length; i++) {
             statistic.increment(testArray[i]);
         }
-        
+
         assertEquals(expectedValue(), statistic.getResult(), getTolerance());
         assertEquals(testArray.length, statistic.getN());
 
         statistic.clear();
-        
+
         // Add testArray all at once and check again
         statistic.incrementAll(testArray);
         assertEquals(expectedValue(), statistic.getResult(), getTolerance());
         assertEquals(testArray.length, statistic.getN());
-        
+
         statistic.clear();
-        
+
         // Cleared
         assertTrue(Double.isNaN(statistic.getResult()));
         assertEquals(0, statistic.getN());
@@ -76,7 +76,7 @@
 
         StorelessUnivariateStatistic statistic =
             (StorelessUnivariateStatistic) getUnivariateStatistic();
-        
+
         TestUtils.checkSerializedEquality(statistic);
 
         statistic.clear();
@@ -84,11 +84,11 @@
         for (int i = 0; i < testArray.length; i++) {
             statistic.increment(testArray[i]);
             if(i % 5 == 0)
-                statistic = (StorelessUnivariateStatistic)TestUtils.serializeAndRecover(statistic); 
+                statistic = (StorelessUnivariateStatistic)TestUtils.serializeAndRecover(statistic);
         }
-        
+
         TestUtils.checkSerializedEquality(statistic);
-        
+
         assertEquals(expectedValue(), statistic.getResult(), getTolerance());
 
         statistic.clear();
@@ -96,53 +96,53 @@
         assertTrue(Double.isNaN(statistic.getResult()));
 
     }
-    
+
     public void testEqualsAndHashCode() {
         StorelessUnivariateStatistic statistic =
             (StorelessUnivariateStatistic) getUnivariateStatistic();
         StorelessUnivariateStatistic statistic2 = null;
-        
+
         assertTrue("non-null, compared to null", !statistic.equals(statistic2));
         assertTrue("reflexive, non-null", statistic.equals(statistic));
-        
+
         int emptyHash = statistic.hashCode();
         statistic2 = (StorelessUnivariateStatistic) getUnivariateStatistic();
         assertTrue("empty stats should be equal", statistic.equals(statistic2));
-        assertEquals("empty stats should have the same hashcode", 
+        assertEquals("empty stats should have the same hashcode",
                 emptyHash, statistic2.hashCode());
-        
+
         statistic.increment(1d);
         assertTrue("reflexive, non-empty", statistic.equals(statistic));
         assertTrue("non-empty, compared to empty", !statistic.equals(statistic2));
         assertTrue("non-empty, compared to empty", !statistic2.equals(statistic));
         assertTrue("non-empty stat should have different hashcode from empty stat",
                 statistic.hashCode() != emptyHash);
-        
+
         statistic2.increment(1d);
         assertTrue("stats with same data should be equal", statistic.equals(statistic2));
-        assertEquals("stats with same data should have the same hashcode", 
+        assertEquals("stats with same data should have the same hashcode",
                 statistic.hashCode(), statistic2.hashCode());
-        
+
         statistic.increment(Double.POSITIVE_INFINITY);
         assertTrue("stats with different n's should not be equal", !statistic2.equals(statistic));
         assertTrue("stats with different n's should have different hashcodes",
                 statistic.hashCode() != statistic2.hashCode());
-        
+
         statistic2.increment(Double.POSITIVE_INFINITY);
         assertTrue("stats with same data should be equal", statistic.equals(statistic2));
-        assertEquals("stats with same data should have the same hashcode", 
-                statistic.hashCode(), statistic2.hashCode()); 
-        
+        assertEquals("stats with same data should have the same hashcode",
+                statistic.hashCode(), statistic2.hashCode());
+
         statistic.clear();
         statistic2.clear();
         assertTrue("cleared stats should be equal", statistic.equals(statistic2));
-        assertEquals("cleared stats should have thashcode of empty stat", 
+        assertEquals("cleared stats should have thashcode of empty stat",
                 emptyHash, statistic2.hashCode());
-        assertEquals("cleared stats should have thashcode of empty stat", 
+        assertEquals("cleared stats should have thashcode of empty stat",
                 emptyHash, statistic.hashCode());
-        
+
     }
-    
+
     public void testMomentSmallSamples() {
         UnivariateStatistic stat = getUnivariateStatistic();
         if (stat instanceof SecondMoment) {
@@ -152,9 +152,9 @@
             assertEquals(0d, moment.getResult(), 0);
         }
     }
-    
-    /** 
-     * Make sure that evaluate(double[]) and inrementAll(double[]), 
+
+    /**
+     * Make sure that evaluate(double[]) and inrementAll(double[]),
      * getResult() give same results.
      */
     public void testConsistency() {
@@ -169,39 +169,39 @@
             TestUtils.assertEquals(stat.getResult(), stat.evaluate(smallSamples[i]), getTolerance());
         }
     }
-    
+
     /**
      * Verifies that copied statistics remain equal to originals when
      * incremented the same way.
      *
      */
     public void testCopyConsistency() {
-        
+
         StorelessUnivariateStatistic master =
             (StorelessUnivariateStatistic) getUnivariateStatistic();
-        
+
         StorelessUnivariateStatistic replica = null;
-        
+
         // Randomly select a portion of testArray to load first
         long index = Math.round((Math.random()) * testArray.length);
-        
+
         // Put first half in master and copy master to replica
         master.incrementAll(testArray, 0, (int) index);
         replica = master.copy();
-        
+
         // Check same
         assertTrue(replica.equals(master));
         assertTrue(master.equals(replica));
-        
+
         // Now add second part to both and check again
-        master.incrementAll(testArray, 
+        master.incrementAll(testArray,
                 (int) index, (int) (testArray.length - index));
-        replica.incrementAll(testArray, 
+        replica.incrementAll(testArray,
                 (int) index, (int) (testArray.length - index));
         assertTrue(replica.equals(master));
         assertTrue(master.equals(replica));
     }
-    
+
     public void testSerial() {
         StorelessUnivariateStatistic s =
             (StorelessUnivariateStatistic) getUnivariateStatistic();

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/SummaryStatisticsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/SummaryStatisticsTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/SummaryStatisticsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/SummaryStatisticsTest.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.
@@ -55,7 +55,7 @@
     public SummaryStatisticsTest(String name) {
         super(name);
     }
-    
+
     protected SummaryStatistics createSummaryStatistics() {
         return new SummaryStatistics();
     }
@@ -77,34 +77,34 @@
         assertEquals("min",min,u.getMin(),tolerance);
         assertEquals("max",max,u.getMax(),tolerance);
         u.clear();
-        assertEquals("total count",0,u.getN(),tolerance);    
-    }     
+        assertEquals("total count",0,u.getN(),tolerance);
+    }
 
     public void testN0andN1Conditions() throws Exception {
         SummaryStatistics u = createSummaryStatistics();
-        assertTrue("Mean of n = 0 set should be NaN", 
+        assertTrue("Mean of n = 0 set should be NaN",
                 Double.isNaN( u.getMean() ) );
-        assertTrue("Standard Deviation of n = 0 set should be NaN", 
+        assertTrue("Standard Deviation of n = 0 set should be NaN",
                 Double.isNaN( u.getStandardDeviation() ) );
-        assertTrue("Variance of n = 0 set should be NaN", 
+        assertTrue("Variance of n = 0 set should be NaN",
                 Double.isNaN(u.getVariance() ) );
 
         /* n=1 */
         u.addValue(one);
-        assertTrue("mean should be one (n = 1)", 
+        assertTrue("mean should be one (n = 1)",
                 u.getMean() == one);
-        assertTrue("geometric should be one (n = 1) instead it is " + u.getGeometricMean(), 
+        assertTrue("geometric should be one (n = 1) instead it is " + u.getGeometricMean(),
                 u.getGeometricMean() == one);
-        assertTrue("Std should be zero (n = 1)", 
+        assertTrue("Std should be zero (n = 1)",
                 u.getStandardDeviation() == 0.0);
-        assertTrue("variance should be zero (n = 1)", 
+        assertTrue("variance should be zero (n = 1)",
                 u.getVariance() == 0.0);
 
-        /* n=2 */               
+        /* n=2 */
         u.addValue(twoF);
-        assertTrue("Std should not be zero (n = 2)", 
+        assertTrue("Std should not be zero (n = 2)",
                 u.getStandardDeviation() != 0.0);
-        assertTrue("variance should not be zero (n = 2)", 
+        assertTrue("variance should not be zero (n = 2)",
                 u.getVariance() != 0.0);
 
     }
@@ -116,25 +116,25 @@
         u.addValue( 3.0 );
         u.addValue( 4.0 );
 
-        assertEquals( "Geometric mean not expected", 2.213364, 
+        assertEquals( "Geometric mean not expected", 2.213364,
                 u.getGeometricMean(), 0.00001 );
     }
 
     public void testNaNContracts() {
         SummaryStatistics u = createSummaryStatistics();
-        assertTrue("mean not NaN",Double.isNaN(u.getMean())); 
-        assertTrue("min not NaN",Double.isNaN(u.getMin())); 
-        assertTrue("std dev not NaN",Double.isNaN(u.getStandardDeviation())); 
-        assertTrue("var not NaN",Double.isNaN(u.getVariance())); 
+        assertTrue("mean not NaN",Double.isNaN(u.getMean()));
+        assertTrue("min not NaN",Double.isNaN(u.getMin()));
+        assertTrue("std dev not NaN",Double.isNaN(u.getStandardDeviation()));
+        assertTrue("var not NaN",Double.isNaN(u.getVariance()));
         assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
 
         u.addValue(1.0);
 
-        assertEquals( "mean not expected", 1.0, 
+        assertEquals( "mean not expected", 1.0,
                 u.getMean(), Double.MIN_VALUE);
-        assertEquals( "variance not expected", 0.0, 
+        assertEquals( "variance not expected", 0.0,
                 u.getVariance(), Double.MIN_VALUE);
-        assertEquals( "geometric mean not expected", 1.0, 
+        assertEquals( "geometric mean not expected", 1.0,
                 u.getGeometricMean(), Double.MIN_VALUE);
 
         u.addValue(-1.0);
@@ -160,7 +160,7 @@
         verifySummary(u, summary);
         u.addValue(2d);
         summary = u.getSummary();
-        verifySummary(u, summary);     
+        verifySummary(u, summary);
     }
 
     public void testSerialization() {
@@ -205,7 +205,7 @@
         u.addValue(4d);
         assertFalse("different n's should make instances not equal", t.equals(u));
         assertFalse("different n's should make instances not equal", u.equals(t));
-        assertTrue("different n's should make hashcodes different", 
+        assertTrue("different n's should make hashcodes different",
                 u.hashCode() != t.hashCode());
 
         //Add data in same order to t
@@ -215,8 +215,8 @@
         t.addValue(4d);
         assertTrue("summaries based on same data should be equal", t.equals(u));
         assertTrue("summaries based on same data should be equal", u.equals(t));
-        assertEquals("summaries based on same data should have same hashcodes", 
-                u.hashCode(), t.hashCode());   
+        assertEquals("summaries based on same data should have same hashcodes",
+                u.hashCode(), t.hashCode());
 
         // Clear and make sure summaries are indistinguishable from empty summary
         u.clear();
@@ -226,7 +226,7 @@
         assertEquals("empty hash code", emptyHash, t.hashCode());
         assertEquals("empty hash code", emptyHash, u.hashCode());
     }
-    
+
     public void testCopy() throws Exception {
         SummaryStatistics u = createSummaryStatistics();
         u.addValue(2d);
@@ -244,7 +244,7 @@
         assertTrue(v.sumsq == v.getSumsqImpl());
         assertTrue(v.sumLog == v.getSumLogImpl());
         assertTrue(v.variance == v.getVarianceImpl());
-        
+
         // Make sure both behave the same with additional values added
         u.addValue(7d);
         u.addValue(9d);
@@ -256,14 +256,14 @@
         v.addValue(23d);
         assertEquals(u, v);
         assertEquals(v, u);
-        
+
         // Check implementation pointers are preserved
         u.clear();
         u.setSumImpl(new Sum());
         SummaryStatistics.copy(u,v);
         assertEquals(u.sum, v.sum);
         assertEquals(u.getSumImpl(), v.getSumImpl());
-        
+
     }
 
     private void verifySummary(SummaryStatistics u, StatisticalSummary s) {
@@ -273,7 +273,7 @@
         TestUtils.assertEquals("std",s.getStandardDeviation(),u.getStandardDeviation(),tolerance);
         TestUtils.assertEquals("mean",s.getMean(),u.getMean(),tolerance);
         TestUtils.assertEquals("min",s.getMin(),u.getMin(),tolerance);
-        TestUtils.assertEquals("max",s.getMax(),u.getMax(),tolerance);   
+        TestUtils.assertEquals("max",s.getMax(),u.getMax(),tolerance);
     }
 
     public void testSetterInjection() throws Exception {
@@ -292,7 +292,7 @@
         u.clear();
         u.setMeanImpl(new Mean()); // OK after clear
     }
-    
+
     public void testSetterIllegalState() throws Exception {
         SummaryStatistics u = createSummaryStatistics();
         u.addValue(1);

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/UnivariateStatisticAbstractTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/UnivariateStatisticAbstractTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/UnivariateStatisticAbstractTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/UnivariateStatisticAbstractTest.java Sat Sep  5 17:36:48 2009
@@ -56,7 +56,7 @@
 
 
     protected double weightedMean = 12.366995073891626d;
-    protected double weightedVar =   9.974760968886391d; 
+    protected double weightedVar =   9.974760968886391d;
     protected double weightedStd = Math.sqrt(weightedVar);
     protected double weightedProduct = 8517647448765288000000d;
     protected double weightedSum = 251.05d;
@@ -111,7 +111,7 @@
                 copy.evaluate(testArray),
                 getTolerance());
     }
-    
+
     /**
      * Tests consistency of weighted statistic computation.
      * For statistics that support weighted evaluation, this test case compares
@@ -120,9 +120,9 @@
      * value appearing only once but with a weight value equal to its multiplicity
      * in the repeating array.
      */
-    
+
     public void testWeightedConsistency() throws Exception {
-        
+
         // See if this statistic computes weighted statistics
         // If not, skip this test
         UnivariateStatistic statistic = getUnivariateStatistic();
@@ -133,23 +133,23 @@
         } catch (NoSuchMethodException ex) {
             return;  // skip test
         }
-        
+
         // Create arrays of values and corresponding integral weights
         // and longer array with values repeated according to the weights
         final int len = 10;        // length of values array
         final double mu = 0;       // mean of test data
-        final double sigma = 5;    // std dev of test data 
+        final double sigma = 5;    // std dev of test data
         double[] values = new double[len];
         double[] weights = new double[len];
-        RandomData randomData = new RandomDataImpl();  
-        
+        RandomData randomData = new RandomDataImpl();
+
         // Fill weights array with random int values between 1 and 5
         int[] intWeights = new int[len];
         for (int i = 0; i < len; i++) {
             intWeights[i] = randomData.nextInt(1, 5);
             weights[i] = intWeights[i];
         }
-        
+
         // Fill values array with random data from N(mu, sigma)
         // and fill valuesList with values from values array with
         // values[i] repeated weights[i] times, each i
@@ -161,21 +161,21 @@
                 valuesList.add(new Double(value));
             }
         }
-        
+
         // Dump valuesList into repeatedValues array
         int sumWeights = valuesList.size();
         double[] repeatedValues = new double[sumWeights];
         for (int i = 0; i < sumWeights; i++) {
             repeatedValues[i] = valuesList.get(i);
         }
-        
+
         // Compare result of weighted statistic computation with direct computation
         // on array of repeated values
         double weightedResult = (Double) evaluateMethod.invoke(
                 statistic, values, weights, 0, values.length);
         TestUtils.assertRelativelyEquals(
-                statistic.evaluate(repeatedValues), weightedResult, 10E-14); 
-        
+                statistic.evaluate(repeatedValues), weightedResult, 10E-14);
+
     }
 
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FirstMomentTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FirstMomentTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FirstMomentTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FirstMomentTest.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.
@@ -27,14 +27,14 @@
 
     /** descriptive statistic. */
     protected FirstMoment stat;
-    
+
     /**
      * @param name
      */
     public FirstMomentTest(String name) {
         super(name);
     }
-    
+
     /**
      * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
      */

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FourthMomentTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FourthMomentTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FourthMomentTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/FourthMomentTest.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.
@@ -27,14 +27,14 @@
 
     /** descriptive statistic. */
     protected FourthMoment stat;
-    
+
     /**
      * @param name
      */
     public FourthMomentTest(String name) {
         super(name);
     }
-    
+
     /**
      * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
      */

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/GeometricMeanTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/GeometricMeanTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/GeometricMeanTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/GeometricMeanTest.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.
@@ -29,7 +29,7 @@
 public class GeometricMeanTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected GeometricMean stat;
-    
+
     /**
      * @param name
      */
@@ -42,7 +42,7 @@
         suite.setName("Mean  Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -58,32 +58,32 @@
     public double expectedValue() {
         return this.geoMean;
     }
-    
+
     public void testSpecialValues() {
         GeometricMean mean = new GeometricMean();
         // empty
         assertTrue(Double.isNaN(mean.getResult()));
-        
+
         // finite data
         mean.increment(1d);
         assertFalse(Double.isNaN(mean.getResult()));
-        
+
         // add 0 -- makes log sum blow to minus infinity, should make 0
         mean.increment(0d);
         assertEquals(0d, mean.getResult(), 0);
-        
+
         // add positive infinity - note the minus infinity above
         mean.increment(Double.POSITIVE_INFINITY);
         assertTrue(Double.isNaN(mean.getResult()));
-        
+
         // clear
         mean.clear();
         assertTrue(Double.isNaN(mean.getResult()));
-        
+
         // positive infinity by itself
         mean.increment(Double.POSITIVE_INFINITY);
         assertEquals(Double.POSITIVE_INFINITY, mean.getResult(), 0);
-        
+
         // negative value -- should make NaN
         mean.increment(-2d);
         assertTrue(Double.isNaN(mean.getResult()));

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/KurtosisTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/KurtosisTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/KurtosisTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/KurtosisTest.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.
@@ -29,14 +29,14 @@
 public class KurtosisTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected Kurtosis stat;
-    
+
     /**
      * @param name
      */
     public KurtosisTest(String name) {
         super(name);
     }
-    
+
     public static Test suite() {
         TestSuite suite = new TestSuite(KurtosisTest.class);
         suite.setName("Kurtosis  Tests");
@@ -58,7 +58,7 @@
     public double expectedValue() {
         return this.kurt;
     }
-    
+
     /**
      * Make sure Double.NaN is returned iff n < 4
      *
@@ -73,7 +73,7 @@
         kurt.increment(1d);
         assertTrue(Double.isNaN(kurt.getResult()));
         kurt.increment(1d);
-        assertFalse(Double.isNaN(kurt.getResult()));      
+        assertFalse(Double.isNaN(kurt.getResult()));
     }
 
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SecondMomentTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SecondMomentTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SecondMomentTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SecondMomentTest.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.
@@ -27,14 +27,14 @@
 
     /** descriptive statistic. */
     protected SecondMoment stat;
-    
+
     /**
      * @param name
      */
     public SecondMomentTest(String name) {
         super(name);
     }
-    
+
     /**
      * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
      */

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SkewnessTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SkewnessTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SkewnessTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/SkewnessTest.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.
@@ -24,13 +24,13 @@
 
 /**
  * Test cases for the {@link UnivariateStatistic} class.
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class SkewnessTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected Skewness stat;
-    
+
     /**
      * @param name
      */
@@ -51,7 +51,7 @@
         suite.setName("Skewness Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -59,7 +59,7 @@
     public double expectedValue() {
         return this.skew;
     }
-    
+
     /**
      * Make sure Double.NaN is returned iff n < 3
      *
@@ -72,7 +72,7 @@
         skew.increment(1d);
         assertTrue(Double.isNaN(skew.getResult()));
         skew.increment(1d);
-        assertFalse(Double.isNaN(skew.getResult()));      
+        assertFalse(Double.isNaN(skew.getResult()));
     }
 
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/StandardDeviationTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/StandardDeviationTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/StandardDeviationTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/StandardDeviationTest.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.
@@ -24,13 +24,13 @@
 
 /**
  * Test cases for the {@link UnivariateStatistic} class.
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class StandardDeviationTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected StandardDeviation stat;
-    
+
     /**
      * @param name
      */
@@ -51,7 +51,7 @@
         suite.setName("StandardDeviation Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -59,7 +59,7 @@
     public double expectedValue() {
         return this.std;
     }
-    
+
     /**
      * Make sure Double.NaN is returned iff n = 0
      *
@@ -70,10 +70,10 @@
         std.increment(1d);
         assertEquals(0d, std.getResult(), 0);
     }
-    
+
     /**
      * Test population version of variance
-     */ 
+     */
     public void testPopulation() {
         double[] values = {-1.0d, 3.1d, 4.0d, -2.1d, 22d, 11.7d, 3d, 14d};
         double sigma = populationStandardDeviation(values);
@@ -85,13 +85,13 @@
         s1.incrementAll(values);
         assertEquals(sigma, s1.getResult(), 1E-14);
         s1 = new StandardDeviation(false, m);
-        assertEquals(sigma, s1.getResult(), 1E-14);     
+        assertEquals(sigma, s1.getResult(), 1E-14);
         s1 = new StandardDeviation(false);
         assertEquals(sigma, s1.evaluate(values), 1E-14);
         s1.incrementAll(values);
-        assertEquals(sigma, s1.getResult(), 1E-14);     
+        assertEquals(sigma, s1.getResult(), 1E-14);
     }
-    
+
     /**
      * Definitional formula for population standard deviation
      */
@@ -99,7 +99,7 @@
         double mean = new Mean().evaluate(v);
         double sum = 0;
         for (int i = 0; i < v.length; i++) {
-            sum += (v[i] - mean) * (v[i] - mean); 
+            sum += (v[i] - mean) * (v[i] - mean);
         }
         return Math.sqrt(sum / v.length);
     }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/ThirdMomentTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/ThirdMomentTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/ThirdMomentTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/ThirdMomentTest.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.
@@ -27,14 +27,14 @@
 
     /** descriptive statistic. */
     protected ThirdMoment stat;
-    
+
     /**
      * @param name
      */
     public ThirdMomentTest(String name) {
         super(name);
     }
-    
+
     /**
      * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
      */

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VarianceTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VarianceTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VarianceTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VarianceTest.java Sat Sep  5 17:36:48 2009
@@ -25,13 +25,13 @@
 
 /**
  * Test cases for the {@link UnivariateStatistic} class.
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class VarianceTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected Variance stat;
-    
+
     /**
      * @param name
      */
@@ -111,19 +111,19 @@
 
     public void testWeightedVariance() {
         Variance variance = new Variance();
-        assertEquals(expectedWeightedValue(), 
+        assertEquals(expectedWeightedValue(),
                 variance.evaluate(testArray, testWeightsArray, 0, testArray.length), getTolerance());
-        
+
         // All weights = 1 -> weighted variance = unweighted variance
         assertEquals(expectedValue(),
                 variance.evaluate(testArray, unitWeightsArray, 0, testArray.length), getTolerance());
-        
+
         // All weights the same -> when weights are normalized to sum to the length of the values array,
         // weighted variance = unweighted value
         assertEquals(expectedValue(),
                 variance.evaluate(testArray, MathUtils.normalizeArray(identicalWeightsArray, testArray.length),
                         0, testArray.length), getTolerance());
-        
+
     }
 
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VectorialCovarianceTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VectorialCovarianceTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VectorialCovarianceTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/moment/VectorialCovarianceTest.java Sat Sep  5 17:36:48 2009
@@ -83,7 +83,7 @@
         VectorialCovariance stat = new VectorialCovariance(points[0].length, true);
         assertEquals(stat, TestUtils.serializeAndRecover(stat));
     }
-    
+
     @Override
     public void setUp() {
         points = new double[][] {

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MaxTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MaxTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MaxTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MaxTest.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.
@@ -29,7 +29,7 @@
 public class MaxTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected Max stat;
-    
+
     /**
      * @param name
      */
@@ -42,7 +42,7 @@
         suite.setName("Max  Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -58,9 +58,9 @@
     public double expectedValue() {
         return this.max;
     }
-    
+
     public void testSpecialValues() {
-        double[] testArray = {0d, Double.NaN, Double.NEGATIVE_INFINITY, 
+        double[] testArray = {0d, Double.NaN, Double.NEGATIVE_INFINITY,
                 Double.POSITIVE_INFINITY};
         Max max = new Max();
         assertTrue(Double.isNaN(max.getResult()));
@@ -72,16 +72,16 @@
         assertEquals(0d, max.getResult(), 0);
         max.increment(testArray[3]);
         assertEquals(Double.POSITIVE_INFINITY, max.getResult(), 0);
-        assertEquals(Double.POSITIVE_INFINITY, max.evaluate(testArray), 0);     
+        assertEquals(Double.POSITIVE_INFINITY, max.evaluate(testArray), 0);
     }
 
     public void testNaNs() {
         Max max = new Max();
         double nan = Double.NaN;
-        assertEquals(3d, max.evaluate(new double[]{nan, 2d, 3d}), 0);     
-        assertEquals(3d, max.evaluate(new double[]{1d, nan, 3d}), 0);     
-        assertEquals(2d, max.evaluate(new double[]{1d, 2d, nan}), 0);     
-        assertTrue(Double.isNaN(max.evaluate(new double[]{nan, nan, nan})));     
+        assertEquals(3d, max.evaluate(new double[]{nan, 2d, 3d}), 0);
+        assertEquals(3d, max.evaluate(new double[]{1d, nan, 3d}), 0);
+        assertEquals(2d, max.evaluate(new double[]{1d, 2d, nan}), 0);
+        assertTrue(Double.isNaN(max.evaluate(new double[]{nan, nan, nan})));
     }
 
 }

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MedianTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MedianTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MedianTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MedianTest.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.
@@ -29,7 +29,7 @@
 public class MedianTest extends UnivariateStatisticAbstractTest{
 
     protected Median stat;
-    
+
     /**
      * @param name
      */
@@ -42,12 +42,12 @@
         suite.setName("Median  Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
     @Override
-    public UnivariateStatistic getUnivariateStatistic() {  
+    public UnivariateStatistic getUnivariateStatistic() {
         return new Median();
     }
 

Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MinTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MinTest.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MinTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/descriptive/rank/MinTest.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.
@@ -29,7 +29,7 @@
 public class MinTest extends StorelessUnivariateStatisticAbstractTest{
 
     protected Min stat;
-    
+
     /**
      * @param name
      */
@@ -42,7 +42,7 @@
         suite.setName("Min  Tests");
         return suite;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -58,9 +58,9 @@
     public double expectedValue() {
         return this.min;
     }
-    
+
     public void testSpecialValues() {
-        double[] testArray = {0d, Double.NaN, Double.POSITIVE_INFINITY, 
+        double[] testArray = {0d, Double.NaN, Double.POSITIVE_INFINITY,
                 Double.NEGATIVE_INFINITY};
         Min min = new Min();
         assertTrue(Double.isNaN(min.getResult()));
@@ -72,16 +72,16 @@
         assertEquals(0d, min.getResult(), 0);
         min.increment(testArray[3]);
         assertEquals(Double.NEGATIVE_INFINITY, min.getResult(), 0);
-        assertEquals(Double.NEGATIVE_INFINITY, min.evaluate(testArray), 0);     
+        assertEquals(Double.NEGATIVE_INFINITY, min.evaluate(testArray), 0);
     }
 
     public void testNaNs() {
         Min min = new Min();
         double nan = Double.NaN;
-        assertEquals(2d, min.evaluate(new double[]{nan, 2d, 3d}), 0);     
-        assertEquals(1d, min.evaluate(new double[]{1d, nan, 3d}), 0);     
-        assertEquals(1d, min.evaluate(new double[]{1d, 2d, nan}), 0);     
-        assertTrue(Double.isNaN(min.evaluate(new double[]{nan, nan, nan})));     
+        assertEquals(2d, min.evaluate(new double[]{nan, 2d, 3d}), 0);
+        assertEquals(1d, min.evaluate(new double[]{1d, nan, 3d}), 0);
+        assertEquals(1d, min.evaluate(new double[]{1d, 2d, nan}), 0);
+        assertTrue(Double.isNaN(min.evaluate(new double[]{nan, nan, nan})));
     }
-    
+
 }



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