/*
 * 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.
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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 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.
/**
 * 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) ).</code>  Therefore, </p>
 * <ul>
 * <li>If any of values are < 0, the result is <code>NaN.</code></li>
 * <li>If all values are non-negative and less than
 * <code>Double.POSITIVE_INFINITY</code>,  but at least one value is 0, the
 * result is <code>0.</code></li>
 * <li>If both <code>Double.POSITIVE_INFINITY</code> and
 * <code>Double.NEGATIVE_INFINITY</code> are among the values, the result is
 * <code>NaN.</code></li>
 * </ul> </p>
 * <p>
 * <strong>Note that this implementation is not synchronized.</strong> If
 * multiple threads access an instance of this class concurrently, and at least
 * one of the threads invokes the <code>increment()</code> or
 * <code>clear()</code> method, it must be synchronized externally.</p>
 *
 *
 */
public class GeometricMean extends AbstractStorelessUnivariateStatistic implements Serializable {

    
Serializable version identifier /** Serializable version identifier */
    private static final long serialVersionUID = -8178734905303459453L;

    
Wrapped SumOfLogs instance /** Wrapped SumOfLogs instance */
    private StorelessUnivariateStatistic sumOfLogs;

    
Create a GeometricMean instance
/**
     * Create a GeometricMean instance
     */
    public GeometricMean() {
        sumOfLogs = new SumOfLogs();
    }

    
Copy constructor, creates a new GeometricMean identical to the original 
Params:
original – the GeometricMean instance to copy
Throws:
NullArgumentException – if original is null/**
     * 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
Params:
sumOfLogs – sum of logs instance to use for computation/**
     * 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}
/**
     * {@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}
/**
     * {@inheritDoc}
     */
    @Override
    public void increment(final double d) {
        sumOfLogs.increment(d);
    }

    
{@inheritDoc}
/**
     * {@inheritDoc}
     */
    @Override
    public double getResult() {
        if (sumOfLogs.getN() > 0) {
            return FastMath.exp(sumOfLogs.getResult() / sumOfLogs.getN());
        } else {
            return Double.NaN;
        }
    }

    
{@inheritDoc}
/**
     * {@inheritDoc}
     */
    @Override
    public void clear() {
        sumOfLogs.clear();
    }

    
Returns the geometric mean of the entries in the specified portion
of the input array.
 See GeometricMean for details on the computing algorithm.

Throws IllegalArgumentException if the array is null.
Params:
values – input array containing the values
begin – first array element to include
length – the number of elements to include
Throws:
MathIllegalArgumentException – if the input array is null or the array
index parameters are not valid
Returns:
the geometric mean or Double.NaN if length = 0 or
any of the values are <= 0./**
     * 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</code> if the array is null.</p>
     *
     * @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 &lt;= 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}
/**
     * {@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 increment has been used to add data; otherwise an IllegalStateException will be thrown.
Params:
sumLogImpl – the StorelessUnivariateStatistic instance to use
for computing the log sum
Throws:
MathIllegalStateException – if data has already been added
 (i.e if n > 0)/**
     * <p>Sets the implementation for the sum of logs.</p>
     * <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 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
Returns:
the StorelessUnivariateStatistic implementing the log sum/**
     * 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.
Params:
source – GeometricMean to copy
dest – GeometricMean to copy to
Throws:
NullArgumentException – if either source or dest is null/**
     * Copies source to dest.
     * <p>Neither source nor dest can be null.</p>
     *
     * @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/**
     * 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());
        }
    }

}