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/*
 * 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.math3.stat.descriptive.moment;

import java.io.Serializable;

import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic;
import org.apache.commons.math3.stat.descriptive.StorelessUnivariateStatistic;
import org.apache.commons.math3.stat.descriptive.summary.SumOfLogs;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.util.MathUtils;

/**
 * Returns the 
 * geometric mean  of the available values.
 * 

* Uses a {@link SumOfLogs} instance to compute sum of logs and returns * exp( 1/n (sum of logs) ). Therefore,

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

*

* 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 increment() or * clear() method, it must be synchronized externally.

* * */ 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 * @throws NullArgumentException if original is null */ public GeometricMean(GeometricMean original) throws NullArgumentException { 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(); // no try-catch or advertised exception because args guaranteed non-null 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 FastMath.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. *

* See {@link GeometricMean} for details on the computing algorithm.

*

* Throws 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 MathIllegalArgumentException 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) throws MathIllegalArgumentException { return FastMath.exp( sumOfLogs.evaluate(values, begin, length) / length); } /** * {@inheritDoc} */ public long getN() { return sumOfLogs.getN(); } /** *

Sets the implementation for the sum of logs.

*

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.

* * @param sumLogImpl the StorelessUnivariateStatistic instance to use * for computing the log sum * @throws MathIllegalStateException if data has already been added * (i.e if n > 0) */ public void setSumLogImpl(StorelessUnivariateStatistic sumLogImpl) throws MathIllegalStateException { 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. *

Neither source nor dest can be null.

* * @param source GeometricMean to copy * @param dest GeometricMean to copy to * @throws NullArgumentException if either source or dest is null */ public static void copy(GeometricMean source, GeometricMean dest) throws NullArgumentException { MathUtils.checkNotNull(source); MathUtils.checkNotNull(dest); dest.setData(source.getDataRef()); dest.sumOfLogs = source.sumOfLogs.copy(); } /** * Throws MathIllegalStateException if n > 0. * @throws MathIllegalStateException if data has been added to this statistic */ private void checkEmpty() throws MathIllegalStateException { if (getN() > 0) { throw new MathIllegalStateException( LocalizedFormats.VALUES_ADDED_BEFORE_CONFIGURING_STATISTIC, getN()); } } }




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