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Commons Math example source code file (GeometricMean.java)

This example Commons Math source code file (GeometricMean.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Java - Commons Math tags/keywords

abstractstorelessunivariatestatistic, geometricmean, geometricmean, io, override, override, serializable, storelessunivariatestatistic, storelessunivariatestatistic, sumoflogs, sumoflogs

The Commons Math GeometricMean.java source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * 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.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math.stat.descriptive.moment;

import java.io.Serializable;

import org.apache.commons.math.MathRuntimeException;
import org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic;
import org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic;
import org.apache.commons.math.stat.descriptive.summary.SumOfLogs;

/**
 * Returns the <a href="http://www.xycoon.com/geometric_mean.htm">
 * geometric mean </a> of the available values.
 * <p>
 * Uses a {@link SumOfLogs} instance to compute sum of logs and returns
 * <code> exp( 1/n  (sum of logs) ).  Therefore, 

* <ul> * <li>If any of values are < 0, the result is NaN. * <li>If all values are non-negative and less than * <code>Double.POSITIVE_INFINITY, but at least one value is 0, the * result is <code>0. * <li>If both Double.POSITIVE_INFINITY and * <code>Double.NEGATIVE_INFINITY are among the values, the result is * <code>NaN. * </ul>

* <p> * <strong>Note that this implementation is not synchronized. If * multiple threads access an instance of this class concurrently, and at least * one of the threads invokes the <code>increment() or * <code>clear() method, it must be synchronized externally.

* * * @version $Revision: 811827 $ $Date: 2009-09-06 11:32:50 -0400 (Sun, 06 Sep 2009) $ */ public class GeometricMean extends AbstractStorelessUnivariateStatistic implements Serializable { /** Serializable version identifier */ private static final long serialVersionUID = -8178734905303459453L; /** Wrapped SumOfLogs instance */ private StorelessUnivariateStatistic sumOfLogs; /** * Create a GeometricMean instance */ public GeometricMean() { sumOfLogs = new SumOfLogs(); } /** * Copy constructor, creates a new {@code GeometricMean} identical * to the {@code original} * * @param original the {@code GeometricMean} instance to copy */ public GeometricMean(GeometricMean original) { super(); copy(original, this); } /** * Create a GeometricMean instance using the given SumOfLogs instance * @param sumOfLogs sum of logs instance to use for computation */ public GeometricMean(SumOfLogs sumOfLogs) { this.sumOfLogs = sumOfLogs; } /** * {@inheritDoc} */ @Override public GeometricMean copy() { GeometricMean result = new GeometricMean(); copy(this, result); return result; } /** * {@inheritDoc} */ @Override public void increment(final double d) { sumOfLogs.increment(d); } /** * {@inheritDoc} */ @Override public double getResult() { if (sumOfLogs.getN() > 0) { return Math.exp(sumOfLogs.getResult() / sumOfLogs.getN()); } else { return Double.NaN; } } /** * {@inheritDoc} */ @Override public void clear() { sumOfLogs.clear(); } /** * Returns the geometric mean of the entries in the specified portion * of the input array. * <p> * See {@link GeometricMean} for details on the computing algorithm.</p> * <p> * Throws <code>IllegalArgumentException if the array is null.

* * @param values input array containing the values * @param begin first array element to include * @param length the number of elements to include * @return the geometric mean or Double.NaN if length = 0 or * any of the values are <= 0. * @throws IllegalArgumentException if the input array is null or the array * index parameters are not valid */ @Override public double evaluate( final double[] values, final int begin, final int length) { return Math.exp( sumOfLogs.evaluate(values, begin, length) / length); } /** * {@inheritDoc} */ public long getN() { return sumOfLogs.getN(); } /** * <p>Sets the implementation for the sum of logs.

* <p>This method must be activated before any data has been added - i.e., * before {@link #increment(double) increment} has been used to add data; * otherwise an IllegalStateException will be thrown.</p> * * @param sumLogImpl the StorelessUnivariateStatistic instance to use * for computing the log sum * @throws IllegalStateException if data has already been added * (i.e if n > 0) */ public void setSumLogImpl( StorelessUnivariateStatistic sumLogImpl) { checkEmpty(); this.sumOfLogs = sumLogImpl; } /** * Returns the currently configured sum of logs implementation * * @return the StorelessUnivariateStatistic implementing the log sum */ public StorelessUnivariateStatistic getSumLogImpl() { return sumOfLogs; } /** * Copies source to dest. * <p>Neither source nor dest can be null.

* * @param source GeometricMean to copy * @param dest GeometricMean to copy to * @throws NullPointerException if either source or dest is null */ public static void copy(GeometricMean source, GeometricMean dest) { dest.sumOfLogs = source.sumOfLogs.copy(); } /** * Throws IllegalStateException if n > 0. */ private void checkEmpty() { if (getN() > 0) { throw MathRuntimeException.createIllegalStateException( "{0} values have been added before statistic is configured", getN()); } } }

Other Commons Math examples (source code examples)

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