1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.math4.legacy.stat.descriptive.moment;
18
19 import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
20 import org.apache.commons.math4.legacy.exception.NullArgumentException;
21 import org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic;
22 import org.apache.commons.math4.legacy.stat.descriptive.WeightedEvaluation;
23 import org.apache.commons.math4.legacy.stat.descriptive.summary.Sum;
24 import org.apache.commons.math4.legacy.core.MathArrays;
25
26 /**
27 * Computes the arithmetic mean of a set of values. Uses the definitional
28 * formula:
29 * <p>
30 * mean = sum(x_i) / n
31 * </p>
32 * <p>where <code>n</code> is the number of observations.
33 * </p>
34 * <p>When {@link #increment(double)} is used to add data incrementally from a
35 * stream of (unstored) values, the value of the statistic that
36 * {@link #getResult()} returns is computed using the following recursive
37 * updating algorithm: </p>
38 * <ol>
39 * <li>Initialize <code>m = </code> the first value</li>
40 * <li>For each additional value, update using <br>
41 * <code>m = m + (new value - m) / (number of observations)</code></li>
42 * </ol>
43 * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
44 * of stored values, a two-pass, corrected algorithm is used, starting with
45 * the definitional formula computed using the array of stored values and then
46 * correcting this by adding the mean deviation of the data values from the
47 * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
48 * Sample Means and Variances," Robert F. Ling, Journal of the American
49 * Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866. </p>
50 * <p>
51 * Returns <code>Double.NaN</code> if the dataset is empty. Note that
52 * Double.NaN may also be returned if the input includes NaN and / or infinite
53 * values.
54 * </p>
55 * <strong>Note that this implementation is not synchronized.</strong> If
56 * multiple threads access an instance of this class concurrently, and at least
57 * one of the threads invokes the <code>increment()</code> or
58 * <code>clear()</code> method, it must be synchronized externally.
59 */
60 public class Mean extends AbstractStorelessUnivariateStatistic
61 implements WeightedEvaluation {
62 /** First moment on which this statistic is based. */
63 protected FirstMoment moment;
64
65 /**
66 * Determines whether or not this statistic can be incremented or cleared.
67 * <p>
68 * Statistics based on (constructed from) external moments cannot
69 * be incremented or cleared.</p>
70 */
71 protected boolean incMoment;
72
73 /** Constructs a Mean. */
74 public Mean() {
75 incMoment = true;
76 moment = new FirstMoment();
77 }
78
79 /**
80 * Constructs a Mean with an External Moment.
81 *
82 * @param m1 the moment
83 */
84 public Mean(final FirstMoment m1) {
85 this.moment = m1;
86 incMoment = false;
87 }
88
89 /**
90 * Copy constructor, creates a new {@code Mean} identical
91 * to the {@code original}.
92 *
93 * @param original the {@code Mean} instance to copy
94 * @throws NullArgumentException if original is null
95 */
96 public Mean(Mean original) throws NullArgumentException {
97 copy(original, this);
98 }
99
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 }