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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.math4.stat.descriptive.moment;
import java.io.Serializable;
import org.apache.commons.math4.exception.MathIllegalArgumentException;
import org.apache.commons.math4.exception.MathIllegalStateException;
import org.apache.commons.math4.exception.NullArgumentException;
import org.apache.commons.math4.exception.util.LocalizedFormats;
import org.apache.commons.math4.stat.descriptive.AbstractStorelessUnivariateStatistic;
import org.apache.commons.math4.stat.descriptive.StorelessUnivariateStatistic;
import org.apache.commons.math4.stat.descriptive.summary.SumOfLogs;
import org.apache.commons.math4.util.FastMath;
import org.apache.commons.math4.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 {@code < 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 = 20150412L;
/** 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}
*/
@Override
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.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());
}
}
}