/*
    * 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
    *
    *      https://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.
   */
  
  /*
   * This is not the original file distributed by the Apache Software Foundation
   * It has been modified by the Hipparchus project
   */
  package org.hipparchus.stat.descriptive.moment;
  
  import java.io.Serializable;
  
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.exception.NullArgumentException;
  import org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic;
  import org.hipparchus.stat.descriptive.AggregatableStatistic;
  import org.hipparchus.stat.descriptive.summary.SumOfLogs;
  import org.hipparchus.util.FastMath;
  import org.hipparchus.util.MathUtils;
  
  /**
   * 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,
   * <ul>
   * <li>If any of values are &lt; 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>
   * <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.
   */
  public class GeometricMean extends AbstractStorelessUnivariateStatistic
      implements AggregatableStatistic<GeometricMean>, Serializable {
  
      /** Serializable version identifier */
      private static final long serialVersionUID = 20150412L;
  
      /** Wrapped SumOfLogs instance */
      private final SumOfLogs sumOfLogs;
  
      /**
       * Determines whether or not this statistic can be incremented or cleared.
       * <p>
       * Statistics based on (constructed from) external statistics cannot
       * be incremented or cleared.
       */
      private final boolean incSumOfLogs;
  
      /**
       * Create a GeometricMean instance.
       */
      public GeometricMean() {
          sumOfLogs = new SumOfLogs();
          incSumOfLogs = true;
      }
  
      /**
       * 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;
          incSumOfLogs = false;
      }
  
      /**
       * 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 {
          MathUtils.checkNotNull(original);
          this.sumOfLogs    = original.sumOfLogs.copy();
          this.incSumOfLogs = original.incSumOfLogs;
     }
 
     /** {@inheritDoc} */
     @Override
     public GeometricMean copy() {
         return new GeometricMean(this);
     }
 
     /** {@inheritDoc} */
     @Override
     public void increment(final double d) {
         if (incSumOfLogs) {
             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() {
         if (incSumOfLogs) {
             sumOfLogs.clear();
         }
     }
 
     /** {@inheritDoc} */
     @Override
     public void aggregate(GeometricMean other) {
         MathUtils.checkNotNull(other);
         if (incSumOfLogs) {
             this.sumOfLogs.aggregate(other.sumOfLogs);
         }
     }
 
     /**
      * 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.
      *
      * @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} */
     @Override
     public long getN() {
         return sumOfLogs.getN();
     }
 
 }