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 */
017package org.apache.commons.math4.legacy.stat.descriptive.moment;
018
019import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
020import org.apache.commons.math4.legacy.exception.NullArgumentException;
021import org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic;
022import org.apache.commons.math4.legacy.stat.descriptive.WeightedEvaluation;
023import org.apache.commons.math4.legacy.stat.descriptive.summary.Sum;
024import org.apache.commons.math4.legacy.core.MathArrays;
025
026/**
027 * Computes the arithmetic mean of a set of values. Uses the definitional
028 * formula:
029 * <p>
030 * mean = sum(x_i) / n
031 * </p>
032 * <p>where <code>n</code> is the number of observations.
033 * </p>
034 * <p>When {@link #increment(double)} is used to add data incrementally from a
035 * stream of (unstored) values, the value of the statistic that
036 * {@link #getResult()} returns is computed using the following recursive
037 * updating algorithm: </p>
038 * <ol>
039 * <li>Initialize <code>m = </code> the first value</li>
040 * <li>For each additional value, update using <br>
041 *   <code>m = m + (new value - m) / (number of observations)</code></li>
042 * </ol>
043 * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
044 * of stored values, a two-pass, corrected algorithm is used, starting with
045 * the definitional formula computed using the array of stored values and then
046 * correcting this by adding the mean deviation of the data values from the
047 * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
048 * Sample Means and Variances," Robert F. Ling, Journal of the American
049 * Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866. </p>
050 * <p>
051 *  Returns <code>Double.NaN</code> if the dataset is empty. Note that
052 *  Double.NaN may also be returned if the input includes NaN and / or infinite
053 *  values.
054 * </p>
055 * <strong>Note that this implementation is not synchronized.</strong> If
056 * multiple threads access an instance of this class concurrently, and at least
057 * one of the threads invokes the <code>increment()</code> or
058 * <code>clear()</code> method, it must be synchronized externally.
059 */
060public class Mean extends AbstractStorelessUnivariateStatistic
061    implements WeightedEvaluation {
062    /** First moment on which this statistic is based. */
063    protected FirstMoment moment;
064
065    /**
066     * Determines whether or not this statistic can be incremented or cleared.
067     * <p>
068     * Statistics based on (constructed from) external moments cannot
069     * be incremented or cleared.</p>
070     */
071    protected boolean incMoment;
072
073    /** Constructs a Mean. */
074    public Mean() {
075        incMoment = true;
076        moment = new FirstMoment();
077    }
078
079    /**
080     * Constructs a Mean with an External Moment.
081     *
082     * @param m1 the moment
083     */
084    public Mean(final FirstMoment m1) {
085        this.moment = m1;
086        incMoment = false;
087    }
088
089    /**
090     * Copy constructor, creates a new {@code Mean} identical
091     * to the {@code original}.
092     *
093     * @param original the {@code Mean} instance to copy
094     * @throws NullArgumentException if original is null
095     */
096    public Mean(Mean original) throws NullArgumentException {
097        copy(original, this);
098    }
099
100    /**
101     * {@inheritDoc}
102     * <p>Note that when {@link #Mean(FirstMoment)} is used to
103     * create a Mean, this method does nothing. In that case, the
104     * FirstMoment should be incremented directly.</p>
105     */
106    @Override
107    public void increment(final double d) {
108        if (incMoment) {
109            moment.increment(d);
110        }
111    }
112
113    /**
114     * {@inheritDoc}
115     */
116    @Override
117    public void clear() {
118        if (incMoment) {
119            moment.clear();
120        }
121    }
122
123    /**
124     * {@inheritDoc}
125     */
126    @Override
127    public double getResult() {
128        return moment.m1;
129    }
130
131    /**
132     * {@inheritDoc}
133     */
134    @Override
135    public long getN() {
136        return moment.getN();
137    }
138
139    /**
140     * Returns the arithmetic mean of the entries in the specified portion of
141     * the input array, or <code>Double.NaN</code> if the designated subarray
142     * is empty.
143     * <p>
144     * Throws <code>IllegalArgumentException</code> if the array is null.</p>
145     * <p>
146     * See {@link Mean} for details on the computing algorithm.</p>
147     *
148     * @param values the input array
149     * @param begin index of the first array element to include
150     * @param length the number of elements to include
151     * @return the mean of the values or Double.NaN if length = 0
152     * @throws MathIllegalArgumentException if the array is null or the array index
153     *  parameters are not valid
154     */
155    @Override
156    public double evaluate(final double[] values, final int begin, final int length)
157        throws MathIllegalArgumentException {
158
159        if (MathArrays.verifyValues(values, begin, length)) {
160            Sum sum = new Sum();
161            double sampleSize = length;
162
163            // Compute initial estimate using definitional formula
164            double xbar = sum.evaluate(values, begin, length) / sampleSize;
165
166            // Compute correction factor in second pass
167            double correction = 0;
168            for (int i = begin; i < begin + length; i++) {
169                correction += values[i] - xbar;
170            }
171            return xbar + (correction/sampleSize);
172        }
173        return Double.NaN;
174    }
175
176    /**
177     * Returns the weighted arithmetic mean of the entries in the specified portion of
178     * the input array, or <code>Double.NaN</code> if the designated subarray
179     * is empty.
180     * <p>
181     * Throws <code>IllegalArgumentException</code> if either array is null.</p>
182     * <p>
183     * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
184     * described above is used here, with weights applied in computing both the original
185     * estimate and the correction factor.</p>
186     * <p>
187     * Throws <code>IllegalArgumentException</code> if any of the following are true:
188     * <ul><li>the values array is null</li>
189     *     <li>the weights array is null</li>
190     *     <li>the weights array does not have the same length as the values array</li>
191     *     <li>the weights array contains one or more infinite values</li>
192     *     <li>the weights array contains one or more NaN values</li>
193     *     <li>the weights array contains negative values</li>
194     *     <li>the start and length arguments do not determine a valid array</li>
195     * </ul>
196     *
197     * @param values the input array
198     * @param weights the weights array
199     * @param begin index of the first array element to include
200     * @param length the number of elements to include
201     * @return the mean of the values or Double.NaN if length = 0
202     * @throws MathIllegalArgumentException if the parameters are not valid
203     * @since 2.1
204     */
205    @Override
206    public double evaluate(final double[] values, final double[] weights,
207                           final int begin, final int length) throws MathIllegalArgumentException {
208        if (MathArrays.verifyValues(values, weights, begin, length)) {
209            Sum sum = new Sum();
210
211            // Compute initial estimate using definitional formula
212            double sumw = sum.evaluate(weights,begin,length);
213            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;
214
215            // Compute correction factor in second pass
216            double correction = 0;
217            for (int i = begin; i < begin + length; i++) {
218                correction += weights[i] * (values[i] - xbarw);
219            }
220            return xbarw + (correction/sumw);
221        }
222        return Double.NaN;
223    }
224
225    /**
226     * Returns the weighted arithmetic mean of the entries in the input array.
227     * <p>
228     * Throws <code>MathIllegalArgumentException</code> if either array is null.</p>
229     * <p>
230     * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
231     * described above is used here, with weights applied in computing both the original
232     * estimate and the correction factor.</p>
233     * <p>
234     * Throws <code>MathIllegalArgumentException</code> if any of the following are true:
235     * <ul><li>the values array is null</li>
236     *     <li>the weights array is null</li>
237     *     <li>the weights array does not have the same length as the values array</li>
238     *     <li>the weights array contains one or more infinite values</li>
239     *     <li>the weights array contains one or more NaN values</li>
240     *     <li>the weights array contains negative values</li>
241     * </ul>
242     *
243     * @param values the input array
244     * @param weights the weights array
245     * @return the mean of the values or Double.NaN if length = 0
246     * @throws MathIllegalArgumentException if the parameters are not valid
247     * @since 2.1
248     */
249    @Override
250    public double evaluate(final double[] values, final double[] weights)
251        throws MathIllegalArgumentException {
252        return evaluate(values, weights, 0, values.length);
253    }
254
255    /**
256     * {@inheritDoc}
257     */
258    @Override
259    public Mean copy() {
260        Mean result = new Mean();
261        // No try-catch or advertised exception because args are guaranteed non-null
262        copy(this, result);
263        return result;
264    }
265
266    /**
267     * Copies source to dest.
268     * <p>Neither source nor dest can be null.</p>
269     *
270     * @param source Mean to copy
271     * @param dest Mean to copy to
272     * @throws NullArgumentException if either source or dest is null
273     */
274    public static void copy(Mean source, Mean dest)
275        throws NullArgumentException {
276        NullArgumentException.check(source);
277        NullArgumentException.check(dest);
278        dest.incMoment = source.incMoment;
279        dest.moment = source.moment.copy();
280    }
281}