Another change to the stored Univariates. The calculations are now abstracted
into an AbstractStoreUnivariate class which take responsibility for all statistical calculations. AbstractStoreUnivariate is implemented by two classes: * StoreUnivariateImpl - This class uses a ExpandableDoubleArray for internal storage. This class is a more efficient class in terms of storage and cycles for users who are interested in gathering statistics not available in the UnivariateImpl implementation. * ListUnivariateImpl - This class is for a situation where a user might wish to maintain a List of numeric objects outside of a StoreUnivariate instance. We still need to add serious error checking in the absence of 1.5's generics, but this implementation will work with any list that contains Number objects - (BigDecimal, BigInteger, Byte, Double, Float, Integer, Long, Short). This implementation ultimately transforms all numeric objects into double primitives via Number.doubleValue(). Becuase AbstractStoreUnivariate does not hold on to any state, a user can add values through the Univariate.addValue() function OR one can directly manipulate the contents of the List directly. git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140830 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Tim O'Brien
parent
52590a7d00
commit
5ae92f12c7
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@ -0,0 +1,252 @@
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/* ====================================================================
|
||||
* The Apache Software License, Version 1.1
|
||||
*
|
||||
* Copyright (c) 2003 The Apache Software Foundation. All rights
|
||||
* reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are permitted provided that the following conditions
|
||||
* are met:
|
||||
*
|
||||
* 1. Redistributions of source code must retain the above copyright
|
||||
* notice, this list of conditions and the following disclaimer.
|
||||
*
|
||||
* 2. Redistributions in binary form must reproduce the above copyright
|
||||
* notice, this list of conditions and the following disclaimer in
|
||||
* the documentation and/or other materials provided with the
|
||||
* distribution.
|
||||
*
|
||||
* 3. The end-user documentation included with the redistribution, if
|
||||
* any, must include the following acknowlegement:
|
||||
* "This product includes software developed by the
|
||||
* Apache Software Foundation (http://www.apache.org/)."
|
||||
* Alternately, this acknowlegement may appear in the software itself,
|
||||
* if and wherever such third-party acknowlegements normally appear.
|
||||
*
|
||||
* 4. The names "The Jakarta Project", "Commons", and "Apache Software
|
||||
* Foundation" must not be used to endorse or promote products derived
|
||||
* from this software without prior written permission. For written
|
||||
* permission, please contact apache@apache.org.
|
||||
*
|
||||
* 5. Products derived from this software may not be called "Apache"
|
||||
* nor may "Apache" appear in their names without prior written
|
||||
* permission of the Apache Software Foundation.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
|
||||
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
|
||||
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
|
||||
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
||||
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
||||
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
|
||||
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
||||
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
|
||||
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
|
||||
* SUCH DAMAGE.
|
||||
* ====================================================================
|
||||
*
|
||||
* This software consists of voluntary contributions made by many
|
||||
* individuals on behalf of the Apache Software Foundation. For more
|
||||
* information on the Apache Software Foundation, please see
|
||||
* <http://www.apache.org/>.
|
||||
*/
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package org.apache.commons.math;
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/**
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* Provides univariate measures for an array of doubles.
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*
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* @author <a href="mailto:tobrien@apache.org">Tim O'Brien</a>
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*/
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public abstract class AbstractStoreUnivariate implements StoreUnivariate {
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/* (non-Javadoc)
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* @see org.apache.commons.math.StoreUnivariate#getMode()
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*/
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public double getMode() {
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// Mode depends on a refactor Freq class
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throw new UnsupportedOperationException("getMode() is not yet implemented");
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.StoreUnivariate#getSkewness()
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*/
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public double getSkewness() {
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// Initialize the skewness
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double skewness = Double.NaN;
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// Get the mean and the standard deviation
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double mean = getMean();
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double stdDev = getStandardDeviation();
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// Sum the cubes of the distance from the mean divided by the standard deviation
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double accum = 0.0;
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for( int i = 0; i < getN(); i++ ) {
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accum += Math.pow( (getElement(i) - mean) / stdDev, 3.0);
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}
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// Get N
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double n = getN();
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// Calculate skewness
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skewness = ( n / ( (n-1) * (n-2) ) ) * accum;
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return skewness;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.StoreUnivariate#getKurtosis()
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*/
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public double getKurtosis() {
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// Initialize the kurtosis
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double kurtosis = Double.NaN;
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// Get the mean and the standard deviation
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double mean = getMean();
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double stdDev = getStandardDeviation();
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// Sum the ^4 of the distance from the mean divided by the standard deviation
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double accum = 0.0;
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for( int i = 0; i < getN(); i++ ) {
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accum += Math.pow( (getElement(i) - mean) / stdDev, 4.0);
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}
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// Get N
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double n = getN();
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double coefficientOne = ( n * (n+1)) / ( (n-1) * (n-2) * (n-3) );
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double termTwo = ( ( 3 * Math.pow( n - 1, 2.0)) / ( (n-2) * (n-3) ) );
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// Calculate kurtosis
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kurtosis = ( coefficientOne * accum ) - termTwo;
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return kurtosis;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.StoreUnivariate#getKurtosisClass()
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*/
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public int getKurtosisClass() {
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int kClass = StoreUnivariate.MESOKURTIC;
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double kurtosis = getKurtosis();
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if( kurtosis > 0 ) {
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kClass = StoreUnivariate.LEPTOKURTIC;
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} else if( kurtosis < 0 ) {
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kClass = StoreUnivariate.PLATYKURTIC;
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}
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return( kClass );
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getMean()
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*/
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public double getMean() {
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double arithMean = getSum() / getN();
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return arithMean;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getVariance()
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*/
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public double getVariance() {
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// Initialize variance
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double variance = Double.NaN;
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if( getN() == 1 ) {
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// If this is a single value
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variance = 0;
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} else if( getN() > 1 ) {
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// Get the mean
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double mean = getMean();
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// Calculate the sum of the squares of the distance between each value and the mean
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double accum = 0.0;
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for( int i = 0; i < getN(); i++ ){
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accum += Math.pow( (getElement(i) - mean), 2.0 );
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}
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// Divide the accumulator by N - Hmmm... unbiased or biased?
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variance = accum / (getN() - 1);
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}
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return variance;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getStandardDeviation()
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*/
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public double getStandardDeviation() {
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double stdDev = Double.NaN;
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if( getN() != 0 ) {
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stdDev = Math.sqrt( getVariance() );
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}
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return( stdDev );
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getMax()
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*/
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public double getMax() {
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// Initialize maximum to NaN
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double max = Double.NaN;
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for( int i = 0; i < getN(); i++) {
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if( i == 0 ) {
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max = getElement(i);
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} else {
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if( getElement(i) > max ) {
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max = getElement(i);
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}
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}
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}
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return max;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getMin()
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*/
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public double getMin() {
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// Initialize minimum to NaN
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double min = Double.NaN;
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for( int i = 0; i < getN(); i++) {
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if( i == 0 ) {
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min = getElement(i);
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} else {
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if( getElement(i) < min ) {
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min = getElement(i);
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}
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}
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}
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return min;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getSum()
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*/
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public double getSum() {
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double accum = 0.0;
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for( int i = 0; i < getN(); i++) {
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accum += getElement(i);
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}
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return accum;
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}
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/* (non-Javadoc)
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* @see org.apache.commons.math.Univariate#getSumsq()
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*/
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public double getSumsq() {
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double accum = 0.0;
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for( int i = 0; i < getN(); i++) {
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accum += Math.pow(getElement(i), 2.0);
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}
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return accum;
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}
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}
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@ -53,6 +53,7 @@
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*/
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package org.apache.commons.math;
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import java.io.Serializable;
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import java.util.NoSuchElementException;
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/**
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@ -60,7 +61,7 @@ import java.util.NoSuchElementException;
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*
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* @author <a href="mailto:tobrien@apache.org">Tim O'Brien</a>
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*/
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public class ExpandableDoubleArray {
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public class ExpandableDoubleArray implements Serializable {
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// This is the internal storage array.
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private double[] internalArray;
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|
|
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@ -0,0 +1,120 @@
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/* ====================================================================
|
||||
* The Apache Software License, Version 1.1
|
||||
*
|
||||
* Copyright (c) 2003 The Apache Software Foundation. All rights
|
||||
* reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are permitted provided that the following conditions
|
||||
* are met:
|
||||
*
|
||||
* 1. Redistributions of source code must retain the above copyright
|
||||
* notice, this list of conditions and the following disclaimer.
|
||||
*
|
||||
* 2. Redistributions in binary form must reproduce the above copyright
|
||||
* notice, this list of conditions and the following disclaimer in
|
||||
* the documentation and/or other materials provided with the
|
||||
* distribution.
|
||||
*
|
||||
* 3. The end-user documentation included with the redistribution, if
|
||||
* any, must include the following acknowlegement:
|
||||
* "This product includes software developed by the
|
||||
* Apache Software Foundation (http://www.apache.org/)."
|
||||
* Alternately, this acknowlegement may appear in the software itself,
|
||||
* if and wherever such third-party acknowlegements normally appear.
|
||||
*
|
||||
* 4. The names "The Jakarta Project", "Commons", and "Apache Software
|
||||
* Foundation" must not be used to endorse or promote products derived
|
||||
* from this software without prior written permission. For written
|
||||
* permission, please contact apache@apache.org.
|
||||
*
|
||||
* 5. Products derived from this software may not be called "Apache"
|
||||
* nor may "Apache" appear in their names without prior written
|
||||
* permission of the Apache Software Foundation.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
|
||||
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
|
||||
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
|
||||
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
||||
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
||||
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
|
||||
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
||||
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
|
||||
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
|
||||
* SUCH DAMAGE.
|
||||
* ====================================================================
|
||||
*
|
||||
* This software consists of voluntary contributions made by many
|
||||
* individuals on behalf of the Apache Software Foundation. For more
|
||||
* information on the Apache Software Foundation, please see
|
||||
* <http://www.apache.org/>.
|
||||
*/
|
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package org.apache.commons.math;
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import java.util.Iterator;
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import java.util.List;
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/**
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* @author <a href="mailto:tobrien@apache.org">Tim O'Brien</a>
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*/
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public class ListUnivariateImpl extends AbstractStoreUnivariate {
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// Holds a reference to a list - GENERICs are going to make
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// out lives easier here as we could only accept List<Number>
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List list;
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public ListUnivariateImpl( List list ) {
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this.list = list;
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}
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|
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/* (non-Javadoc)
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* @see org.apache.commons.math.StoreUnivariate#getValues()
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*/
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public double[] getValues() {
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double[] copiedArray = new double[list.size()];
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int i = 0;
|
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Iterator it = list.iterator();
|
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while( it.hasNext() ) {
|
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Number n = (Number) it.next();
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copiedArray[i] = n.doubleValue();
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i++;
|
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}
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|
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return copiedArray;
|
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}
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|
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/* (non-Javadoc)
|
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* @see org.apache.commons.math.StoreUnivariate#getElement(int)
|
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*/
|
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public double getElement(int index) {
|
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Number n = (Number) list.get(index);
|
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return n.doubleValue();
|
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}
|
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|
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/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getN()
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*/
|
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public double getN() {
|
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return list.size();
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}
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|
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/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#addValue(double)
|
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*/
|
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public void addValue(double v) {
|
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list.add( new Double(v));
|
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}
|
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|
||||
/* (non-Javadoc)
|
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* @see org.apache.commons.math.Univariate#clear()
|
||||
*/
|
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public void clear() {
|
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list.clear();
|
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}
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|
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}
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|
|
@ -114,5 +114,13 @@ public interface StoreUnivariate extends Univariate {
|
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*
|
||||
* @return returns the current set of numbers in the order in which they were added to this set
|
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*/
|
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public abstract double[] getValues();
|
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|
||||
/**
|
||||
* Returns the element at the specified index
|
||||
*
|
||||
* @return return the element at the specified index
|
||||
*/
|
||||
public abstract double getElement(int index);
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -54,11 +54,9 @@
|
|||
package org.apache.commons.math;
|
||||
|
||||
/**
|
||||
* Provides univariate measures for an array of doubles.
|
||||
*
|
||||
* @author <a href="mailto:tobrien@apache.org">Tim O'Brien</a>
|
||||
*/
|
||||
public class StoreUnivariateImpl implements StoreUnivariate {
|
||||
public class StoreUnivariateImpl extends AbstractStoreUnivariate {
|
||||
|
||||
ExpandableDoubleArray eDA;
|
||||
|
||||
|
|
@ -66,207 +64,36 @@ public class StoreUnivariateImpl implements StoreUnivariate {
|
|||
eDA = new ExpandableDoubleArray();
|
||||
}
|
||||
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.StoreUnivariate#getMode()
|
||||
* @see org.apache.commons.math.StoreUnivariate#getValues()
|
||||
*/
|
||||
public double getMode() {
|
||||
// Mode depends on a refactor Freq class
|
||||
throw new UnsupportedOperationException("getMode() is not yet implemented");
|
||||
public double[] getValues() {
|
||||
|
||||
double[] copiedArray = new double[ eDA.getNumElements() ];
|
||||
System.arraycopy( eDA.getValues(), 0, copiedArray, 0, eDA.getNumElements());
|
||||
return copiedArray;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.StoreUnivariate#getSkewness()
|
||||
* @see org.apache.commons.math.StoreUnivariate#getElement(int)
|
||||
*/
|
||||
public double getSkewness() {
|
||||
// Initialize the skewness
|
||||
double skewness = Double.NaN;
|
||||
|
||||
// Get the mean and the standard deviation
|
||||
double mean = getMean();
|
||||
double stdDev = getStandardDeviation();
|
||||
|
||||
// Sum the cubes of the distance from the mean divided by the standard deviation
|
||||
double accum = 0.0;
|
||||
for( int i = 0; i < eDA.getNumElements(); i++ ) {
|
||||
accum += Math.pow( (eDA.getElement(i) - mean) / stdDev, 3.0);
|
||||
}
|
||||
|
||||
// Get N
|
||||
double n = getN();
|
||||
|
||||
// Calculate skewness
|
||||
skewness = ( n / ( (n-1) * (n-2) ) ) * accum;
|
||||
|
||||
return skewness;
|
||||
public double getElement(int index) {
|
||||
return eDA.getElement(index);
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.StoreUnivariate#getKurtosis()
|
||||
*/
|
||||
public double getKurtosis() {
|
||||
// Initialize the kurtosis
|
||||
double kurtosis = Double.NaN;
|
||||
|
||||
// Get the mean and the standard deviation
|
||||
double mean = getMean();
|
||||
double stdDev = getStandardDeviation();
|
||||
|
||||
// Sum the ^4 of the distance from the mean divided by the standard deviation
|
||||
double accum = 0.0;
|
||||
for( int i = 0; i < eDA.getNumElements(); i++ ) {
|
||||
accum += Math.pow( (eDA.getElement(i) - mean) / stdDev, 4.0);
|
||||
}
|
||||
|
||||
// Get N
|
||||
double n = getN();
|
||||
|
||||
double coefficientOne = ( n * (n+1)) / ( (n-1) * (n-2) * (n-3) );
|
||||
double termTwo = ( ( 3 * Math.pow( n - 1, 2.0)) / ( (n-2) * (n-3) ) );
|
||||
// Calculate kurtosis
|
||||
kurtosis = ( coefficientOne * accum ) - termTwo;
|
||||
|
||||
return kurtosis;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.StoreUnivariate#getKurtosisClass()
|
||||
*/
|
||||
public int getKurtosisClass() {
|
||||
|
||||
int kClass = StoreUnivariate.MESOKURTIC;
|
||||
|
||||
double kurtosis = getKurtosis();
|
||||
if( kurtosis > 0 ) {
|
||||
kClass = StoreUnivariate.LEPTOKURTIC;
|
||||
} else if( kurtosis < 0 ) {
|
||||
kClass = StoreUnivariate.PLATYKURTIC;
|
||||
}
|
||||
|
||||
return( kClass );
|
||||
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#addValue(double)
|
||||
*/
|
||||
public void addValue(double v) {
|
||||
eDA.addElement( v );
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getMean()
|
||||
*/
|
||||
public double getMean() {
|
||||
double arithMean = getSum() / getN();
|
||||
return arithMean;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getVariance()
|
||||
*/
|
||||
public double getVariance() {
|
||||
// Initialize variance
|
||||
double variance = Double.NaN;
|
||||
|
||||
if( getN() == 1 ) {
|
||||
// If this is a single value
|
||||
variance = 0;
|
||||
} else if( getN() > 1 ) {
|
||||
// Get the mean
|
||||
double mean = getMean();
|
||||
|
||||
// Calculate the sum of the squares of the distance between each value and the mean
|
||||
double accum = 0.0;
|
||||
for( int i = 0; i < eDA.getNumElements(); i++ ){
|
||||
accum += Math.pow( (eDA.getElement(i) - mean), 2.0 );
|
||||
}
|
||||
|
||||
// Divide the accumulator by N - Hmmm... unbiased or biased?
|
||||
variance = accum / (getN() - 1);
|
||||
}
|
||||
|
||||
return variance;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getStandardDeviation()
|
||||
*/
|
||||
public double getStandardDeviation() {
|
||||
double stdDev = Double.NaN;
|
||||
if( getN() != 0 ) {
|
||||
stdDev = Math.sqrt( getVariance() );
|
||||
}
|
||||
return( stdDev );
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getMax()
|
||||
*/
|
||||
public double getMax() {
|
||||
|
||||
// Initialize maximum to NaN
|
||||
double max = Double.NaN;
|
||||
|
||||
for( int i = 0; i < eDA.getNumElements(); i++) {
|
||||
if( i == 0 ) {
|
||||
max = eDA.getElement(i);
|
||||
} else {
|
||||
if( eDA.getElement(i) > max ) {
|
||||
max = eDA.getElement(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return max;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getMin()
|
||||
*/
|
||||
public double getMin() {
|
||||
// Initialize minimum to NaN
|
||||
double min = Double.NaN;
|
||||
|
||||
for( int i = 0; i < eDA.getNumElements(); i++) {
|
||||
if( i == 0 ) {
|
||||
min = eDA.getElement(i);
|
||||
} else {
|
||||
if( eDA.getElement(i) < min ) {
|
||||
min = eDA.getElement(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return min;
|
||||
}
|
||||
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getN()
|
||||
*/
|
||||
public double getN() {
|
||||
return eDA.getNumElements();
|
||||
}
|
||||
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getSum()
|
||||
* @see org.apache.commons.math.Univariate#addValue(double)
|
||||
*/
|
||||
public double getSum() {
|
||||
double accum = 0.0;
|
||||
for( int i = 0; i < eDA.getNumElements(); i++) {
|
||||
accum += eDA.getElement(i);
|
||||
}
|
||||
return accum;
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
* @see org.apache.commons.math.Univariate#getSumsq()
|
||||
*/
|
||||
public double getSumsq() {
|
||||
double accum = 0.0;
|
||||
for( int i = 0; i < eDA.getNumElements(); i++) {
|
||||
accum += Math.pow(eDA.getElement(i), 2.0);
|
||||
}
|
||||
return accum;
|
||||
public void addValue(double v) {
|
||||
eDA.addElement( v );
|
||||
}
|
||||
|
||||
/* (non-Javadoc)
|
||||
|
|
|
|||
|
|
@ -53,6 +53,8 @@
|
|||
*/
|
||||
package org.apache.commons.math;
|
||||
|
||||
import java.io.Serializable;
|
||||
|
||||
/**
|
||||
*
|
||||
* Accumulates univariate statistics for values fed in
|
||||
|
|
@ -62,10 +64,10 @@ package org.apache.commons.math;
|
|||
* to doubles by addValue().
|
||||
*
|
||||
* @author Phil Steitz
|
||||
* @version $Revision: 1.1 $ $Date: 2003/05/15 05:39:00 $
|
||||
* @version $Revision: 1.2 $ $Date: 2003/05/15 06:33:19 $
|
||||
*
|
||||
*/
|
||||
public class UnivariateImpl implements Univariate {
|
||||
public class UnivariateImpl implements Univariate, Serializable {
|
||||
|
||||
/** running sum of values that have been added */
|
||||
private double sum = 0.0;
|
||||
|
|
|
|||
|
|
@ -0,0 +1,156 @@
|
|||
/* ====================================================================
|
||||
* The Apache Software License, Version 1.1
|
||||
*
|
||||
* Copyright (c) 2003 The Apache Software Foundation. All rights
|
||||
* reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are permitted provided that the following conditions
|
||||
* are met:
|
||||
*
|
||||
* 1. Redistributions of source code must retain the above copyright
|
||||
* notice, this list of conditions and the following disclaimer.
|
||||
*
|
||||
* 2. Redistributions in binary form must reproduce the above copyright
|
||||
* notice, this list of conditions and the following disclaimer in
|
||||
* the documentation and/or other materials provided with the
|
||||
* distribution.
|
||||
*
|
||||
* 3. The end-user documentation included with the redistribution, if
|
||||
* any, must include the following acknowlegement:
|
||||
* "This product includes software developed by the
|
||||
* Apache Software Foundation (http://www.apache.org/)."
|
||||
* Alternately, this acknowlegement may appear in the software itself,
|
||||
* if and wherever such third-party acknowlegements normally appear.
|
||||
*
|
||||
* 4. The names "The Jakarta Project", "Commons", and "Apache Software
|
||||
* Foundation" must not be used to endorse or promote products derived
|
||||
* from this software without prior written permission. For written
|
||||
* permission, please contact apache@apache.org.
|
||||
*
|
||||
* 5. Products derived from this software may not be called "Apache"
|
||||
* nor may "Apache" appear in their names without prior written
|
||||
* permission of the Apache Software Foundation.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
|
||||
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
|
||||
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
|
||||
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
||||
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
||||
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
|
||||
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
||||
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
|
||||
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
|
||||
* SUCH DAMAGE.
|
||||
* ====================================================================
|
||||
*
|
||||
* This software consists of voluntary contributions made by many
|
||||
* individuals on behalf of the Apache Software Foundation. For more
|
||||
* information on the Apache Software Foundation, please see
|
||||
* <http://www.apache.org/>.
|
||||
*/
|
||||
package org.apache.commons.math;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.Collection;
|
||||
import java.util.List;
|
||||
|
||||
import junit.framework.Test;
|
||||
import junit.framework.TestCase;
|
||||
import junit.framework.TestSuite;
|
||||
|
||||
/**
|
||||
* Test cases for the {@link Univariate} class.
|
||||
*
|
||||
* @author <a href="mailto:phil@steitz.com">Phil Steitz</a>
|
||||
* @version $Revision: 1.1 $ $Date: 2003/05/15 06:33:19 $
|
||||
*/
|
||||
|
||||
public final class ListUnivariateImplTest extends TestCase {
|
||||
private double one = 1;
|
||||
private float two = 2;
|
||||
private int three = 3;
|
||||
|
||||
private double mean = 2;
|
||||
private double sumSq = 18;
|
||||
private double sum = 8;
|
||||
private double var = 0.666666666666666666667;
|
||||
private double std = Math.sqrt(var);
|
||||
private double n = 4;
|
||||
private double min = 1;
|
||||
private double max = 3;
|
||||
private double skewness = 0;
|
||||
private double kurtosis = 0.5;
|
||||
private int kClass = StoreUnivariate.LEPTOKURTIC;
|
||||
private double tolerance = 10E-15;
|
||||
|
||||
public ListUnivariateImplTest(String name) {
|
||||
super(name);
|
||||
}
|
||||
|
||||
public void setUp() {
|
||||
}
|
||||
|
||||
public static Test suite() {
|
||||
TestSuite suite = new TestSuite(ListUnivariateImplTest.class);
|
||||
suite.setName("Freq Tests");
|
||||
return suite;
|
||||
}
|
||||
|
||||
/** test stats */
|
||||
public void testStats() {
|
||||
List externalList = new ArrayList();
|
||||
|
||||
StoreUnivariate u = new ListUnivariateImpl( externalList );
|
||||
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(two);
|
||||
u.addValue(two);
|
||||
u.addValue(three);
|
||||
assertEquals("N",n,u.getN(),tolerance);
|
||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
||||
assertEquals("var",var,u.getVariance(),tolerance);
|
||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
||||
assertEquals("min",min,u.getMin(),tolerance);
|
||||
assertEquals("max",max,u.getMax(),tolerance);
|
||||
u.clear();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
}
|
||||
|
||||
public void testN0andN1Conditions() throws Exception {
|
||||
List list = new ArrayList();
|
||||
|
||||
StoreUnivariate 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() ) );
|
||||
|
||||
list.add( new Double(one));
|
||||
|
||||
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);
|
||||
}
|
||||
|
||||
public void testSkewAndKurtosis() {
|
||||
StoreUnivariate u = new StoreUnivariateImpl();
|
||||
|
||||
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);
|
||||
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue