001    /*
002     * Licensed to the Apache Software Foundation (ASF) under one or more
003     * contributor license agreements.  See the NOTICE file distributed with
004     * this work for additional information regarding copyright ownership.
005     * The ASF licenses this file to You under the Apache License, Version 2.0
006     * (the "License"); you may not use this file except in compliance with
007     * the License.  You may obtain a copy of the License at
008     *
009     *      http://www.apache.org/licenses/LICENSE-2.0
010     *
011     * Unless required by applicable law or agreed to in writing, software
012     * distributed under the License is distributed on an "AS IS" BASIS,
013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014     * See the License for the specific language governing permissions and
015     * limitations under the License.
016     */
017    package org.apache.commons.math.stat.descriptive.moment;
018    
019    import java.io.Serializable;
020    
021    import org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic;
022    import org.apache.commons.math.stat.descriptive.WeightedEvaluation;
023    import org.apache.commons.math.stat.descriptive.summary.Sum;
024    
025    /**
026     * <p>Computes the arithmetic mean of a set of values. Uses the definitional
027     * formula:</p>
028     * <p>
029     * mean = sum(x_i) / n
030     * </p>
031     * <p>where <code>n</code> is the number of observations.
032     * </p>
033     * <p>When {@link #increment(double)} is used to add data incrementally from a
034     * stream of (unstored) values, the value of the statistic that
035     * {@link #getResult()} returns is computed using the following recursive
036     * updating algorithm: </p>
037     * <ol>
038     * <li>Initialize <code>m = </code> the first value</li>
039     * <li>For each additional value, update using <br>
040     *   <code>m = m + (new value - m) / (number of observations)</code></li>
041     * </ol>
042     * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
043     * of stored values, a two-pass, corrected algorithm is used, starting with
044     * the definitional formula computed using the array of stored values and then
045     * correcting this by adding the mean deviation of the data values from the
046     * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
047     * Sample Means and Variances," Robert F. Ling, Journal of the American
048     * Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866. </p>
049     * <p>
050     *  Returns <code>Double.NaN</code> if the dataset is empty.
051     * </p>
052     * <strong>Note that this implementation is not synchronized.</strong> If
053     * multiple threads access an instance of this class concurrently, and at least
054     * one of the threads invokes the <code>increment()</code> or
055     * <code>clear()</code> method, it must be synchronized externally.
056     *
057     * @version $Revision: 1006299 $ $Date: 2010-10-10 16:47:17 +0200 (dim. 10 oct. 2010) $
058     */
059    public class Mean extends AbstractStorelessUnivariateStatistic
060        implements Serializable, WeightedEvaluation {
061    
062        /** Serializable version identifier */
063        private static final long serialVersionUID = -1296043746617791564L;
064    
065        /** First moment on which this statistic is based. */
066        protected FirstMoment moment;
067    
068        /**
069         * Determines whether or not this statistic can be incremented or cleared.
070         * <p>
071         * Statistics based on (constructed from) external moments cannot
072         * be incremented or cleared.</p>
073         */
074        protected boolean incMoment;
075    
076        /** Constructs a Mean. */
077        public Mean() {
078            incMoment = true;
079            moment = new FirstMoment();
080        }
081    
082        /**
083         * Constructs a Mean with an External Moment.
084         *
085         * @param m1 the moment
086         */
087        public Mean(final FirstMoment m1) {
088            this.moment = m1;
089            incMoment = false;
090        }
091    
092        /**
093         * Copy constructor, creates a new {@code Mean} identical
094         * to the {@code original}
095         *
096         * @param original the {@code Mean} instance to copy
097         */
098        public Mean(Mean original) {
099            copy(original, this);
100        }
101    
102        /**
103         * {@inheritDoc}
104         */
105        @Override
106        public void increment(final double d) {
107            if (incMoment) {
108                moment.increment(d);
109            }
110        }
111    
112        /**
113         * {@inheritDoc}
114         */
115        @Override
116        public void clear() {
117            if (incMoment) {
118                moment.clear();
119            }
120        }
121    
122        /**
123         * {@inheritDoc}
124         */
125        @Override
126        public double getResult() {
127            return moment.m1;
128        }
129    
130        /**
131         * {@inheritDoc}
132         */
133        public long getN() {
134            return moment.getN();
135        }
136    
137        /**
138         * Returns the arithmetic mean of the entries in the specified portion of
139         * the input array, or <code>Double.NaN</code> if the designated subarray
140         * is empty.
141         * <p>
142         * Throws <code>IllegalArgumentException</code> if the array is null.</p>
143         * <p>
144         * See {@link Mean} for details on the computing algorithm.</p>
145         *
146         * @param values the input array
147         * @param begin index of the first array element to include
148         * @param length the number of elements to include
149         * @return the mean of the values or Double.NaN if length = 0
150         * @throws IllegalArgumentException if the array is null or the array index
151         *  parameters are not valid
152         */
153        @Override
154        public double evaluate(final double[] values,final int begin, final int length) {
155            if (test(values, begin, length)) {
156                Sum sum = new Sum();
157                double sampleSize = length;
158    
159                // Compute initial estimate using definitional formula
160                double xbar = sum.evaluate(values, begin, length) / sampleSize;
161    
162                // Compute correction factor in second pass
163                double correction = 0;
164                for (int i = begin; i < begin + length; i++) {
165                    correction += values[i] - xbar;
166                }
167                return xbar + (correction/sampleSize);
168            }
169            return Double.NaN;
170        }
171    
172        /**
173         * Returns the weighted arithmetic mean of the entries in the specified portion of
174         * the input array, or <code>Double.NaN</code> if the designated subarray
175         * is empty.
176         * <p>
177         * Throws <code>IllegalArgumentException</code> if either array is null.</p>
178         * <p>
179         * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
180         * described above is used here, with weights applied in computing both the original
181         * estimate and the correction factor.</p>
182         * <p>
183         * Throws <code>IllegalArgumentException</code> if any of the following are true:
184         * <ul><li>the values array is null</li>
185         *     <li>the weights array is null</li>
186         *     <li>the weights array does not have the same length as the values array</li>
187         *     <li>the weights array contains one or more infinite values</li>
188         *     <li>the weights array contains one or more NaN values</li>
189         *     <li>the weights array contains negative values</li>
190         *     <li>the start and length arguments do not determine a valid array</li>
191         * </ul></p>
192         *
193         * @param values the input array
194         * @param weights the weights array
195         * @param begin index of the first array element to include
196         * @param length the number of elements to include
197         * @return the mean of the values or Double.NaN if length = 0
198         * @throws IllegalArgumentException if the parameters are not valid
199         * @since 2.1
200         */
201        public double evaluate(final double[] values, final double[] weights,
202                               final int begin, final int length) {
203            if (test(values, weights, begin, length)) {
204                Sum sum = new Sum();
205    
206                // Compute initial estimate using definitional formula
207                double sumw = sum.evaluate(weights,begin,length);
208                double xbarw = sum.evaluate(values, weights, begin, length) / sumw;
209    
210                // Compute correction factor in second pass
211                double correction = 0;
212                for (int i = begin; i < begin + length; i++) {
213                    correction += weights[i] * (values[i] - xbarw);
214                }
215                return xbarw + (correction/sumw);
216            }
217            return Double.NaN;
218        }
219    
220        /**
221         * Returns the weighted arithmetic mean of the entries in the input array.
222         * <p>
223         * Throws <code>IllegalArgumentException</code> if either array is null.</p>
224         * <p>
225         * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
226         * described above is used here, with weights applied in computing both the original
227         * estimate and the correction factor.</p>
228         * <p>
229         * Throws <code>IllegalArgumentException</code> if any of the following are true:
230         * <ul><li>the values array is null</li>
231         *     <li>the weights array is null</li>
232         *     <li>the weights array does not have the same length as the values array</li>
233         *     <li>the weights array contains one or more infinite values</li>
234         *     <li>the weights array contains one or more NaN values</li>
235         *     <li>the weights array contains negative values</li>
236         * </ul></p>
237         *
238         * @param values the input array
239         * @param weights the weights array
240         * @return the mean of the values or Double.NaN if length = 0
241         * @throws IllegalArgumentException if the parameters are not valid
242         * @since 2.1
243         */
244        public double evaluate(final double[] values, final double[] weights) {
245            return evaluate(values, weights, 0, values.length);
246        }
247    
248        /**
249         * {@inheritDoc}
250         */
251        @Override
252        public Mean copy() {
253            Mean result = new Mean();
254            copy(this, result);
255            return result;
256        }
257    
258    
259        /**
260         * Copies source to dest.
261         * <p>Neither source nor dest can be null.</p>
262         *
263         * @param source Mean to copy
264         * @param dest Mean to copy to
265         * @throws NullPointerException if either source or dest is null
266         */
267        public static void copy(Mean source, Mean dest) {
268            dest.setData(source.getDataRef());
269            dest.incMoment = source.incMoment;
270            dest.moment = source.moment.copy();
271        }
272    }