Consolidated AbstractDescriptiveStatistics into DescriptiveStatistics. Added Serialization interfaces where required.

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141258 13f79535-47bb-0310-9956-ffa450edef68

src/java/org/apache/commons/math/stat/univariate/AbstractDescriptiveStatistics.java

@@ -1,179 +0,0 @@
-/*
- * Copyright 2003-2004 The Apache Software Foundation.
- * 
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.apache.commons.math.stat.univariate;
-
-import java.util.Arrays;
-
-import org.apache.commons.math.stat.univariate.moment.GeometricMean;
-import org.apache.commons.math.stat.univariate.moment.Kurtosis;
-import org.apache.commons.math.stat.univariate.moment.Mean;
-import org.apache.commons.math.stat.univariate.moment.Skewness;
-import org.apache.commons.math.stat.univariate.moment.Variance;
-import org.apache.commons.math.stat.univariate.rank.Max;
-import org.apache.commons.math.stat.univariate.rank.Min;
-import org.apache.commons.math.stat.univariate.rank.Percentile;
-import org.apache.commons.math.stat.univariate.summary.Sum;
-import org.apache.commons.math.stat.univariate.summary.SumOfSquares;
-
-/**
- * Abstract superclass for DescriptiveStatistics implementations. 
- * 
- * @version $Revision: 1.3 $ $Date: 2004/05/23 00:56:15 $
- */
-public abstract class AbstractDescriptiveStatistics
-    extends DescriptiveStatistics {
-        
-    /**
-     * Create an AbstractDescriptiveStatistics
-     */
-    protected AbstractDescriptiveStatistics() {
-        super();
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getSum()
-     */
-    public double getSum() {
-    	return apply(new Sum());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getSumsq()
-     */
-    public double getSumsq() {
-    	return apply(new SumOfSquares());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getMean()
-     */
-    public double getMean() {
-    	return apply(new Mean());
-    }
-
-    /**
-    * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getStandardDeviation()
-     */
-    public double getStandardDeviation() {
-    	double stdDev = Double.NaN;
-    	if (getN() > 0) {
-    		if (getN() > 1) {
-    			stdDev = Math.sqrt(getVariance());
-    		} else {
-    			stdDev = 0.0;
-    		}
-    	}
-    	return (stdDev);
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getVariance()
-     */
-    public double getVariance() {
-    	return apply(new Variance());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getSkewness()
-     */
-    public double getSkewness() {
-    	return apply(new Skewness());
-    }
-
-    /**
-      * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getKurtosis()
-     */
-    public double getKurtosis() {
-    	return apply(new Kurtosis());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getMax()
-     */
-    public double getMax() {
-    	return apply(new Max());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getMin()
-     */
-    public double getMin() {
-    	return apply(new Min());
-    }
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getGeometricMean()
-     */
-    public double getGeometricMean() {
-    	return apply(new GeometricMean());
-    }
-    
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getPercentile(double)
-     */
-    public double getPercentile(double p) {
-    	return apply(new Percentile(p));
-    }
-    
-    /**
-     * Generates a text report displaying
-     * univariate statistics from values that
-     * have been added.
-     * @return String with line feeds displaying statistics
-     */
-    public String toString() {
-    	StringBuffer outBuffer = new StringBuffer();
-    	outBuffer.append("UnivariateImpl:\n");
-    	outBuffer.append("n: " + getN() + "\n");
-    	outBuffer.append("min: " + getMin() + "\n");
-    	outBuffer.append("max: " + getMax() + "\n");
-    	outBuffer.append("mean: " + getMean() + "\n");
-    	outBuffer.append("std dev: " + getStandardDeviation() + "\n");
-    	outBuffer.append("skewness: " + getSkewness() + "\n");
-    	outBuffer.append("kurtosis: " + getKurtosis() + "\n");
-    	return outBuffer.toString();
-    }
-    
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getSortedValues()
-     */
-    public double[] getSortedValues() {
-        double[] sort = getValues();
-        Arrays.sort(sort);
-        return sort;
-    }
-    
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#addValue(double)
-     */
-    public abstract void addValue(double value);
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getValues()
-     */
-    public abstract double[] getValues();
-
-    /**
-     * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#getElement(int)
-     */
-    public abstract double getElement(int index);
-    
-    /**
-      * @see org.apache.commons.math.stat.univariate.DescriptiveStatistics#apply(UnivariateStatistic)
-     */
-    public abstract double apply(UnivariateStatistic stat);
-    
-}

src/java/org/apache/commons/math/stat/univariate/AbstractStorelessUnivariateStatistic.java

@@ -15,18 +15,23 @@
  */
 package org.apache.commons.math.stat.univariate;
 
+import java.io.Serializable;
+
 /**
  *
  * Abstract Implementation for the {@link StorelessUnivariateStatistic} interface.
  * <p>
  * Provides a default <code>evaluate()</code> implementation.
  * 
- * @version $Revision: 1.14 $ $Date: 2004/03/21 21:57:18 $
+ * @version $Revision: 1.15 $ $Date: 2004/06/01 21:34:35 $
  */
 public abstract class AbstractStorelessUnivariateStatistic
     extends AbstractUnivariateStatistic
-    implements StorelessUnivariateStatistic {
+    implements StorelessUnivariateStatistic, Serializable {
 
+    /** Serialization UID */
+    static final long serialVersionUID = -44915725420072521L;
+    
     /**
      * This default implementation just calls {@link #increment} in a loop over the input array and 
      * then {@link #getResult} to compute the return value.  

src/java/org/apache/commons/math/stat/univariate/AbstractUnivariateStatistic.java

@@ -15,14 +15,19 @@
  */
 package org.apache.commons.math.stat.univariate;
 
+import java.io.Serializable;
+
 /**
  * Abstract Implementation for UnivariateStatistics.
  * Provides the ability to extend polymophically so that
  * indiviual statistics do not need to implement these methods.
- * @version $Revision: 1.16 $ $Date: 2004/04/27 16:42:34 $
+ * @version $Revision: 1.17 $ $Date: 2004/06/01 21:34:35 $
  */
 public abstract class AbstractUnivariateStatistic
-    implements UnivariateStatistic {
+    implements UnivariateStatistic, Serializable {
+    
+    /** Serialization UID */
+    static final long serialVersionUID = -8007759382851708045L;
 
     /**
      * @see org.apache.commons.math.stat.univariate.UnivariateStatistic#evaluate(double[])

src/java/org/apache/commons/math/stat/univariate/DescriptiveStatistics.java

@@ -16,17 +16,31 @@
 package org.apache.commons.math.stat.univariate;
 
 import java.io.Serializable;
+import java.util.Arrays;
 
 import org.apache.commons.discovery.tools.DiscoverClass;
+import org.apache.commons.math.stat.univariate.moment.GeometricMean;
+import org.apache.commons.math.stat.univariate.moment.Kurtosis;
+import org.apache.commons.math.stat.univariate.moment.Mean;
+import org.apache.commons.math.stat.univariate.moment.Skewness;
+import org.apache.commons.math.stat.univariate.moment.Variance;
+import org.apache.commons.math.stat.univariate.rank.Max;
+import org.apache.commons.math.stat.univariate.rank.Min;
+import org.apache.commons.math.stat.univariate.rank.Percentile;
+import org.apache.commons.math.stat.univariate.summary.Sum;
+import org.apache.commons.math.stat.univariate.summary.SumOfSquares;
 
 
 /**
  * Abstract factory class for univariate statistical summaries.
  * 
- * @version $Revision: 1.5 $ $Date: 2004/05/23 00:56:15 $
+ * @version $Revision: 1.6 $ $Date: 2004/06/01 21:34:35 $
  */
-public abstract class DescriptiveStatistics implements Serializable, StatisticalSummary {
+public abstract class DescriptiveStatistics implements StatisticalSummary, Serializable {
-
+    
+    /** Serialization UID */
+    static final long serialVersionUID = 5188298269533339922L;
+    
 	/**
 	 * Create an instance of a <code>DescriptiveStatistics</code>
      * @param cls the type of <code>DescriptiveStatistics</code> object to
@@ -94,7 +108,9 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
 	 * arithmetic mean </a> of the available values 
 	 * @return The mean or Double.NaN if no values have been added.
 	 */
-	public abstract double getMean();
+    public double getMean() {
+    	return apply(new Mean());
+    }
 
 	/** 
 	 * Returns the <a href="http://www.xycoon.com/geometric_mean.htm">
@@ -102,21 +118,35 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
 	 * @return The geometricMean, Double.NaN if no values have been added, 
 	 * or if the productof the available values is less than or equal to 0.
 	 */
-	public abstract double getGeometricMean();
+    public double getGeometricMean() {
+    	return apply(new GeometricMean());
+    }
 
 	/** 
 	 * Returns the variance of the available values.
 	 * @return The variance, Double.NaN if no values have been added 
 	 * or 0.0 for a single value set.  
 	 */
-	public abstract double getVariance();
+    public double getVariance() {
+    	return apply(new Variance());
+    }
 
 	/** 
 	 * Returns the standard deviation of the available values.
 	 * @return The standard deviation, Double.NaN if no values have been added 
 	 * or 0.0 for a single value set. 
 	 */
-	public abstract double getStandardDeviation();
+    public double getStandardDeviation() {
+    	double stdDev = Double.NaN;
+    	if (getN() > 0) {
+    		if (getN() > 1) {
+    			stdDev = Math.sqrt(getVariance());
+    		} else {
+    			stdDev = 0.0;
+    		}
+    	}
+    	return (stdDev);
+    }
 
 	/**
 	 * Returns the skewness of the available values. Skewness is a 
@@ -124,7 +154,9 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
 	 * @return The skewness, Double.NaN if no values have been added 
 	 * or 0.0 for a value set &lt;=2. 
 	 */
-	public abstract double getSkewness();
+    public double getSkewness() {
+    	return apply(new Skewness());
+    }
 
 	/**
 	 * Returns the Kurtosis of the available values. Kurtosis is a 
@@ -132,19 +164,25 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
 	 * @return The kurtosis, Double.NaN if no values have been added, or 0.0 
 	 * for a value set &lt;=3. 
 	 */
-	public abstract double getKurtosis();
+    public double getKurtosis() {
+    	return apply(new Kurtosis());
+    }
 
 	/** 
 	 * Returns the maximum of the available values
 	 * @return The max or Double.NaN if no values have been added.
 	 */
-	public abstract double getMax();
+    public double getMax() {
+    	return apply(new Max());
+    }
 
 	/** 
 	* Returns the minimum of the available values
 	* @return The min or Double.NaN if no values have been added.
 	*/
-	public abstract double getMin();
+    public double getMin() {
+    	return apply(new Min());
+    }
 
 	/** 
 	 * Returns the number of available values
@@ -156,14 +194,18 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
 	 * Returns the sum of the values that have been added to Univariate.
 	 * @return The sum or Double.NaN if no values have been added
 	 */
-	public abstract double getSum();
+    public double getSum() {
+    	return apply(new Sum());
+    }
 
 	/**
 	 * Returns the sum of the squares of the available values.
 	 * @return The sum of the squares or Double.NaN if no 
 	 * values have been added.
 	 */
-	public abstract double getSumsq();
+    public double getSumsq() {
+    	return apply(new SumOfSquares());
+    }
 
 	/** 
 	 * Resets all statistics and storage
@@ -208,7 +250,11 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
      * @return returns the current set of 
      * numbers sorted in ascending order        
      */
-	public abstract double[] getSortedValues();
+    public double[] getSortedValues() {
+        double[] sort = getValues();
+        Arrays.sort(sort);
+        return sort;
+    }
 
     /**
      * Returns the element at the specified index
@@ -234,8 +280,29 @@ public abstract class DescriptiveStatistics implements Serializable, Statistical
      * @return An estimate for the pth percentile of the stored data 
      * values
      */
-	public abstract double getPercentile(double p);
+    public double getPercentile(double p) {
+    	return apply(new Percentile(p));
+    }
 	
+    /**
+     * Generates a text report displaying
+     * univariate statistics from values that
+     * have been added.
+     * @return String with line feeds displaying statistics
+     */
+    public String toString() {
+    	StringBuffer outBuffer = new StringBuffer();
+    	outBuffer.append("UnivariateImpl:\n");
+    	outBuffer.append("n: " + getN() + "\n");
+    	outBuffer.append("min: " + getMin() + "\n");
+    	outBuffer.append("max: " + getMax() + "\n");
+    	outBuffer.append("mean: " + getMean() + "\n");
+    	outBuffer.append("std dev: " + getStandardDeviation() + "\n");
+    	outBuffer.append("skewness: " + getSkewness() + "\n");
+    	outBuffer.append("kurtosis: " + getKurtosis() + "\n");
+    	return outBuffer.toString();
+    }
+    
 	/**
 	 * Apply the given statistic to the data associated with this set of statistics.
 	 * @param stat the statistic to apply

src/java/org/apache/commons/math/stat/univariate/DescriptiveStatisticsImpl.java

@@ -23,10 +23,13 @@ import org.apache.commons.math.util.ContractableDoubleArray;
  * Default implementation of
  * {@link org.apache.commons.math.stat.univariate.DescriptiveStatistics}.
  * 
- * @version $Revision: 1.5 $ $Date: 2004/05/23 00:30:01 $
+ * @version $Revision: 1.6 $ $Date: 2004/06/01 21:34:35 $
  */
-public class DescriptiveStatisticsImpl extends AbstractDescriptiveStatistics implements Serializable {
+public class DescriptiveStatisticsImpl extends DescriptiveStatistics implements Serializable {
 
+    /** Serializable version identifier */
+    static final long serialVersionUID = -1868088725461221010L;
+    
 	/** hold the window size **/
 	protected int windowSize;
     

src/java/org/apache/commons/math/stat/univariate/SummaryStatistics.java

@@ -22,10 +22,13 @@ import org.apache.commons.discovery.tools.DiscoverClass;
 /**
  * Abstract factory class for univariate statistical summaries.
  * 
- * @version $Revision: 1.5 $ $Date: 2004/05/19 14:16:31 $
+ * @version $Revision: 1.6 $ $Date: 2004/06/01 21:34:35 $
  */
-public abstract class SummaryStatistics implements Serializable, StatisticalSummary {
+public abstract class SummaryStatistics implements StatisticalSummary, Serializable {
 
+    /** Serialization UID */
+    static final long serialVersionUID = -6400596334135654825L;
+    
 	/**
 	 * Create an instance of a <code>SummaryStatistics</code>
      * @param cls the type of <code>SummaryStatistics</code> object to

src/java/org/apache/commons/math/stat/univariate/SummaryStatisticsImpl.java

@@ -15,6 +15,7 @@
  */
 package org.apache.commons.math.stat.univariate;
 
+import java.io.Serializable;
 import org.apache.commons.math.stat.univariate.moment.SecondMoment;
 import org.apache.commons.math.stat.univariate.moment.GeometricMean;
 import org.apache.commons.math.stat.univariate.moment.Mean;
@@ -28,9 +29,12 @@ import org.apache.commons.math.stat.univariate.summary.SumOfSquares;
 /**
  * Provides a default {@link SummaryStatistics} implementation.
  * 
- * @version $Revision: 1.2 $ $Date: 2004/04/27 04:37:59 $  
+ * @version $Revision: 1.3 $ $Date: 2004/06/01 21:34:35 $  
  */
-public class SummaryStatisticsImpl extends SummaryStatistics {
+public class SummaryStatisticsImpl extends SummaryStatistics implements Serializable {
+
+    /** Serializable version identifier */
+    static final long serialVersionUID = 8787174276883311692L;
 
     /** count of values that have been added */
     protected long n = 0;