001 /*
002 * Java Genetic Algorithm Library (jenetics-4.4.0).
003 * Copyright (c) 2007-2019 Franz Wilhelmstötter
004 *
005 * Licensed under the Apache License, Version 2.0 (the "License");
006 * you may not use this file except in compliance with the License.
007 * 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 * Author:
018 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
019 */
020 package io.jenetics.stat;
021
022 import static java.util.Objects.requireNonNull;
023 import static io.jenetics.internal.util.Hashes.hash;
024
025 import java.io.Serializable;
026 import java.util.function.ToLongFunction;
027 import java.util.stream.Collector;
028
029 /**
030 * <i>Value</i> objects which contains statistical moments.
031 *
032 * @see io.jenetics.stat.LongMomentStatistics
033 *
034 * @implNote
035 * This class is immutable and thread-safe.
036 *
037 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
038 * @since 3.0
039 * @version 4.1
040 */
041 public final class LongMoments implements Serializable {
042
043 private static final long serialVersionUID = 1L;
044
045 private final long _count;
046 private final long _min;
047 private final long _max;
048 private final long _sum;
049 private final double _mean;
050 private final double _variance;
051 private final double _skewness;
052 private final double _kurtosis;
053
054
055 /**
056 * Create an immutable object which contains statistical values.
057 *
058 * @param count the count of values recorded
059 * @param min the minimum value
060 * @param max the maximum value
061 * @param sum the sum of the recorded values
062 * @param mean the arithmetic mean of values
063 * @param variance the variance of values
064 * @param skewness the skewness of values
065 * @param kurtosis the kurtosis of values
066 */
067 private LongMoments(
068 final long count,
069 final long min,
070 final long max,
071 final long sum,
072 final double mean,
073 final double variance,
074 final double skewness,
075 final double kurtosis
076 ) {
077 _count = count;
078 _min = min;
079 _max = max;
080 _sum = sum;
081 _mean = mean;
082 _variance = variance;
083 _skewness = skewness;
084 _kurtosis = kurtosis;
085 }
086
087 /**
088 * Returns the count of values recorded.
089 *
090 * @return the count of recorded values
091 */
092 public long getCount() {
093 return _count;
094 }
095
096 /**
097 * Return the minimum value recorded, or {@code Long.MAX_VALUE} if no
098 * values have been recorded.
099 *
100 * @return the minimum value, or {@code Long.MAX_VALUE} if none
101 */
102 public long getMin() {
103 return _min;
104 }
105
106 /**
107 * Return the maximum value recorded, or {@code Long.MIN_VALUE} if no
108 * values have been recorded.
109 *
110 * @return the maximum value, or {@code Long.MIN_VALUE} if none
111 */
112 public long getMax() {
113 return _max;
114 }
115
116 /**
117 * Return the sum of values recorded, or zero if no values have been
118 * recorded.
119 *
120 * @return the sum of values, or zero if none
121 */
122 public long getSum() {
123 return _sum;
124 }
125
126 /**
127 * Return the arithmetic mean of values recorded, or zero if no values have
128 * been recorded.
129 *
130 * @return the arithmetic mean of values, or zero if none
131 */
132 public double getMean() {
133 return _mean;
134 }
135
136 /**
137 * Return the variance of values recorded, or {@code Double.NaN} if no
138 * values have been recorded.
139 *
140 * @return the variance of values, or {@code NaN} if none
141 */
142 public double getVariance() {
143 return _variance;
144 }
145
146 /**
147 * Return the skewness of values recorded, or {@code Double.NaN} if less
148 * than two values have been recorded.
149 *
150 * @see <a href="https://en.wikipedia.org/wiki/Skewness">Skewness</a>
151 *
152 * @return the skewness of values, or {@code NaN} if less than two values
153 * have been recorded
154 */
155 public double getSkewness() {
156 return _skewness;
157 }
158
159 /**
160 * Return the kurtosis of values recorded, or {@code Double.NaN} if less
161 * than four values have been recorded.
162 *
163 * @see <a href="https://en.wikipedia.org/wiki/Kurtosis">Kurtosis</a>
164 *
165 * @return the kurtosis of values, or {@code NaN} if less than four values
166 * have been recorded
167 */
168 public double getKurtosis() {
169 return _kurtosis;
170 }
171
172 @Override
173 public int hashCode() {
174 return
175 hash(_count,
176 hash(_sum,
177 hash(_min,
178 hash(_max,
179 hash(_mean,
180 hash(_variance,
181 hash(_skewness,
182 hash(_kurtosis,
183 hash(getClass())))))))));
184 }
185
186 @Override
187 public boolean equals(final Object obj) {
188 return obj == this ||
189 obj instanceof LongMoments &&
190 _count == ((LongMoments)obj)._count &&
191 _sum == ((LongMoments)obj)._sum &&
192 _min == ((LongMoments)obj)._min &&
193 _max == ((LongMoments)obj)._max &&
194 Double.compare(_mean, ((LongMoments)obj)._mean) == 0 &&
195 Double.compare(_variance, ((LongMoments)obj)._variance) == 0 &&
196 Double.compare(_skewness, ((LongMoments)obj)._skewness) == 0 &&
197 Double.compare(_kurtosis, ((LongMoments)obj)._kurtosis) == 0;
198 }
199
200 @Override
201 public String toString() {
202 return String.format(
203 "LongMoments[N=%d, ∧=%s, ∨=%s, Σ=%s, μ=%s, s²=%s, S=%s, K=%s]",
204 getCount(), getMin(), getMax(), getSum(),
205 getMean(), getVariance(), getSkewness(), getKurtosis()
206 );
207 }
208
209 /**
210 * Create an immutable object which contains statistical values.
211 *
212 * @param count the count of values recorded
213 * @param min the minimum value
214 * @param max the maximum value
215 * @param sum the sum of the recorded values
216 * @param mean the arithmetic mean of values
217 * @param variance the variance of values
218 * @param skewness the skewness of values
219 * @param kurtosis the kurtosis of values
220 * @return an immutable object which contains statistical values
221 */
222 public static LongMoments of(
223 final long count,
224 final long min,
225 final long max,
226 final long sum,
227 final double mean,
228 final double variance,
229 final double skewness,
230 final double kurtosis
231 ) {
232 return new LongMoments(
233 count,
234 min,
235 max,
236 sum,
237 mean,
238 variance,
239 skewness,
240 kurtosis
241 );
242 }
243
244 /**
245 * Return a new value object of the statistical moments, currently
246 * represented by the {@code statistics} object.
247 *
248 * @param statistics the creating (mutable) statistics class
249 * @return the statistical moments
250 */
251 public static LongMoments of(final LongMomentStatistics statistics) {
252 return new LongMoments(
253 statistics.getCount(),
254 statistics.getMin(),
255 statistics.getMax(),
256 statistics.getSum(),
257 statistics.getMean(),
258 statistics.getVariance(),
259 statistics.getSkewness(),
260 statistics.getKurtosis()
261 );
262 }
263
264 /**
265 * Return a {@code Collector} which returns moments-statistics for the
266 * resulting values.
267 *
268 * <pre>{@code
269 * final Stream<Long> stream = ...
270 * final LongMoments moments = stream.collect(toLongMoments()));
271 * }</pre>
272 *
273 * @since 4.1
274 *
275 * @param <N> the type of the input elements
276 * @return a {@code Collector} implementing the moments-statistics reduction
277 */
278 public static <N extends Number> Collector<N, ?, LongMoments>
279 toLongMoments() {
280 return toLongMoments(Number::longValue);
281 }
282
283 /**
284 * Return a {@code Collector} which applies an long-producing mapping
285 * function to each input element, and returns moments-statistics for the
286 * resulting values.
287 *
288 * <pre>{@code
289 * final Stream<SomeObject> stream = ...
290 * final LongMoments moments = stream
291 * .collect(toLongMoments(v -> v.longValue()));
292 * }</pre>
293 *
294 * @param mapper a mapping function to apply to each element
295 * @param <T> the type of the input elements
296 * @return a {@code Collector} implementing the moments-statistics reduction
297 * @throws java.lang.NullPointerException if the given {@code mapper} is
298 * {@code null}
299 */
300 public static <T> Collector<T, ?, LongMoments>
301 toLongMoments(final ToLongFunction<? super T> mapper) {
302 requireNonNull(mapper);
303 return Collector.of(
304 LongMomentStatistics::new,
305 (a, b) -> a.accept(mapper.applyAsLong(b)),
306 LongMomentStatistics::combine,
307 LongMoments::of
308 );
309 }
310
311 }
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